Data science and analysis Books

Book SynopsisA new and important contribution to the re-emergent field of comparative anthropology, this book argues that comparative ethnographic methods are essential for more contextually sophisticated accounts of a number of pressing human concerns today. The book includes expert accounts from an international team of scholars, showing how these methods can be used to illuminate important theoretical and practical projects. Illustrated with examples of successful inter-disciplinary projects, it highlights the challenges, benefits, and innovative strategies involved in working collaboratively across disciplines. Through its focus on practical methodological and logistical accounts, it will be of value to both seasoned researchers who seek practical models for conducting their own cutting-edge comparative research, and to teachers and students who are looking for first-person accounts of comparative ethnographic research.Trade Review'Comparison is almost as fundamental to the human mind as air and water is to the body. It is therefore puzzling and paradoxical that anthropology, which was founded as an explicitly comparative discipline, has often been ambivalent, reluctant and even hostile to comparative research. This extremely timely book reinstates comparison as a key element in anthropological theory and methodology, demonstrating a variety in comparative strategies which reflect the diversity of anthropology itself and, indeed, the human world. Highly recommended.' Thomas Hylland Eriksen, University of Oslo'This book engages with a welcome and timely project: restoring comparative perspectives to anthropology. By exploring the challenges, dimensions, and complexities of comparative methodologies, it illustrates how critical comparisons can inform theory and illuminate underlying political economic and institutional processes.' Nina Glick Schiller, Max Planck Institute for Social AnthropologyTable of ContentsIntroduction. Comparative ethnography: its promise, process, and successful implementations Edward D. Lowe and Michael Schnegg; Part I. Binary Comparisons: 1. Thinking with comparison in the anthropology/historical anthropology of migration Caroline B. Brettell; 2. Comparing tangerines: Dorothy Lee and the search for an authentic individualism Richard Handler; 3. A comparative ethnographic study of suicide epidemics in two Pacific Island societies Edward D. Lowe; Part II. Regional Comparisons: 4. The comparison of structures and the comparison of systems: Lévi-Strauss, Dumont, Luhmann Guido Sprenger; 5. Regional comparison in historical anthropology: three case examples from South Arabia Andre Gingrich; 6. Scaling ethnography up Michael Schnegg; Part III. Distant and Fluid Comparisons: 7. Best, worst, and good enough: lessons learned from multi-sited comparative ethnography Jennifer S. Hirsch, Holly Wardlow, Daniel Jordan Smith, Harriet Phinney, Shanti Parikh and Constance A. Nathanson; 8. Research across cultures and disciplines: methodological challenges in an interdisciplinary and comparative research project on emotion socialization Birgitt Röttger-Rössler; 9. Global sport industries, comparison, and economics of scales Niko Besnier and Daniel Guinness.

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Book SynopsisThis is a book on public opinion told through the eyes of the pollster. It looks at public opinion as a concept and in historical context then turns to the use of public opinion practically as an analytic input; particularly, how to use it to forecast, convince, and assess.

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Book SynopsisLearn by doing with this user-friendly introduction to time series data analysis in R. This book explores the intricacies of managing and cleaning time series data of different sizes, scales and granularity, data preparation for analysis and visualization, and different approaches to classical and machine learning time series modeling and forecasting. A range of pedagogical features support students, including end-of-chapter exercises, problems, quizzes and case studies. The case studies are designed to stretch the learner, introducing larger data sets, enhanced data management skills, and R packages and functions appropriate for real-world data analysis. On top of providing commented R programs and data sets, the book''s companion website offers extra case studies, lecture slides, videos and exercise solutions. Accessible to those with a basic background in statistics and probability, this is an ideal hands-on text for undergraduate and graduate students, as well as researchers in data-rich disciplinesTrade Review'This book provides an excellent introduction to time series modelling and forecasting which are increasingly important tools in the domain of official statistics. The clear descriptions and real-life examples provided in this text make it easy to digest for those not already familiar with the topic. In addition, the exercises allow readers to develop their understanding in more depth through hands-on applications of the methods to real data using open-source tools. The inclusion of modern topics such as machine learning and artificial intelligence are a valuable addition to make the text relevant and comprehensive.' Steve Matthews, Statistics Canada'This book is a great introduction to the ideas and methods of time series data analysis. Chapter by chapter, it will show you its most valuable features, like the wealth of real examples as well as practical uses of R and graphical visualization. You will certainly enjoy this text, as it is suitable for a wide range of statistical courses.' Vera Ioudina, Texas State University'Lots of good real world examples together with the use of R helps a lot as do the nice set of exercises. In time series, it is a tricky balance between overdoing theory or just hand waving and here the author does very well. This would make a lovely course text!' Gareth Janacek, University of East Anglia'Time Series for Data Scientists' develops your intuition before walking through classical and modern time series methods in easy-to-understand terms. With each algorithm Dr. Sanchez first helps you understand the motivation behind the approach; then walks you through the formulas step-by-step, outlining what we're doing and why; she also includes R code to help you apply the techniques learned to solve real-world business problems using real-world data sets; and takes the time to show you how to interpret the output, and discuss what to try next when an initial approach doesn't quite match the trends in the data. Whether you're an undergraduate or graduate student, are curious about time series methods, are looking for a self-paced book, or a reference guide, this is a must-have.' Irina Kukuyeva, Fractional Chief Data Officer'A fine textbook for an introductory time series course aimed at undergraduates in Statistics or Data Science. The author did an excellent work in the choice of topics, covering from classical exploratory techniques to modern machine learning approaches, while keeping the level of the exposition accessible to readers with a modicum of mathematical background. To be recommended!' Giovanni Petris, University of Arkansas'This book should be a serious contender if you are looking for an introductory text for an undergraduate course in time series. It is especially suited for a course populated with students having varying degrees of mathematical skill levels. Its conversational approach to introducing time series concepts and the use of insightful examples throughout the book makes it very accessible to students who are not highly trained in abstract mathematical reasoning. Nevertheless, it does not shy away from providing the theoretical underpinnings of various time series models but does so in a manner very accessible to students. The availability of R code throughout the book is an added plus. Even if I am teaching an upper-level graduate course in time series, I would use this book as a supplement simply because of the plethora of examples and data sources it provides.' V. A. Samaranayake, Missouri University of Science and TechnologyTable of ContentsPart I. Descriptive Features of Time Series Data: 1. Introduction to time series data; 2. Smoothing and decomposing a time series; 3. Summary statistics of stationary time series; Part II. Univariate Models of Temporal Dependence: 4. The algebra of differencing and backshifting; 5. Stationary stochastic processes; 6. ARIMA(p,d,q)(P,D,Q)$_F$ modeling and forecasting; Part III. Multivariate Modeling and Forecasting: 7. Latent process models for time series; 8. Vector autoregression; 9. Classical regression with ARMA residuals; 10. Machine learning methods for time series; References; Index.

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Book SynopsisAs a result of the COVID-19 pandemic, medical statistics and public health data have become staples of newsfeeds worldwide, with infection rates, deaths, case fatality and the mysterious R figure featuring regularly. However, we don''t all have the statistical background needed to translate this information into knowledge. In this lively account, Stephen Senn explains these statistical phenomena and demonstrates how statistics is essential to making rational decisions about medical care. The second edition has been thoroughly updated to cover developments of the last two decades and includes a new chapter on medical statistical challenges of COVID-19, along with additional material on infectious disease modelling and representation of women in clinical trials. Senn entertains with anecdotes, puzzles and paradoxes, while tackling big themes including: clinical trials and the development of medicines, life tables, vaccines and their risks or lack of them, smoking and lung cancer, and even the power of prayer.Trade Review'The COVID pandemic has shown the power of statistics to save millions of lives by revealing 'what works'. Yet statistical methods have a deeply controversial history, and provoke sometimes bitter debate to this day. Professor Stephen Senn is renowned for his brilliant insights on the subject, and in Dicing with Death he offers us a series of fascinating journeys through its vast and varied landscape.' Robert Matthews, Visiting Professor Aston University and author of Chancing It: The Laws of Chance and How They Can Work for YouTable of Contents1. Circling the square; 2. The diceman cometh; 3. Trials of life; 4. Of dice and men; 5. Sex and the single patient; 6. A hale view of pills (and other matters); 7. Time's tables; 8. A dip in the pool; 9. The things that bug us; 10. The law is a ass; 11. The empire of the sum; 12. Going viral; Notes; Index.

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Book SynopsisA clear easy-to-read guide to presenting your message using statistical data Poor presentation of data is everywhere; basic principles are forgotten or ignored. As a result, audiences are presented with confusing tables and charts that do not make immediate sense. This book is intended to be read by all who present data in any form. The author, a chartered statistician who has run many courses on the subject of data presentation, presents numerous examples alongside an explanation of how improvements can be made and basic principles to adopt. He advocates following four key C' words in all messages: Clear, Concise, Correct and Consistent. Following the principles in the book will lead to clearer, simpler and easier to understand messages which can then be assimilated faster. Anyone from student to researcher, journalist to policy adviser, charity worker to government statistician, will benefit from reading this book. More importantly, it will also benefit the reTrade Review�Highly recommended to a very wide audience.� (Mathematical Association of America, 1 January 2015) �Presenting data is, of course, more than a good table or an informative graphic. The words that describe the data must also be correct, clear, concise and consistent, and the author devotes a chapter to ensuring that the expert�s hard work is not undone by commentary that is too technical or too laboured to be understood by non-expert audiences.� (The Royal Statistical Society, 1 February 2015) �This book must be mandatory to any data analyst and statistician, and indeed anyone who presents numeric data. The word "numeric" is important, as non-numeric data are not discussed in the book.� (ENBIS News, 10 December 2014) �The words that describe the data, and the messages it may have, must also be correct, clear, concise and consistent, and the author devotes a chapter to ensuring that the expert�s hard work is not undone by commentary that is too technical or too laboured to be understood by non-expert audiences.� (Significance, 1 February 2014) "The book is easy to read and can be consumed in a single train journey. It is also easy to look at and the illustrations and graphics occupy as much space as the text. The author has indeed put his money where his mouth is and the graphics both illustrate his points and makes them alone. The highlight for me was in the chapter on tables where the author reduces a table containing seven columns and five rows to a two by two table which beautifully makes the point when previously it had been lost in a forest of figures... This is an excellent book and I would recommend it as essential reading to anyone who is writing a thesis or dissertation, making a presentation or writing a paper. That�s all of us." (Occupational Medicine, 15th February 2016)Table of ContentsList of Tables vii List of Figures ix Introduction xiii Preface xvii Acknowledgements xix 1 Understanding number 1 1.1 Thousands separator 2 1.2 Decimal separator 3 1.3 Level of detail in comparisons 4 1.4 Justification of data 5 1.5 Basic rounding 7 1.6 Effective rounding 9 Notes 16 2 Tables 17 2.1 Position of totals in tables 17 2.2 What is a table? 19 2.3 Reference tables 19 2.4 Summary tables 22 2.5 How tables are read 24 2.6 Layout of data in tables 25 2.7 Capital letters for table titles and headings in tables 29 2.8 Use of bold typeface 30 2.9 Use of gridlines and other lines in tables 30 Notes 31 3 Charts (bar charts, histograms, pie charts, graphs) 33 3.1 How the user interprets charts 33 3.2 Written aims for charts 35 3.3 Scale definition and display 37 3.4 Difference between bar charts and histograms 49 3.5 Pie chart principles 51 3.6 Issues with pie charts 55 3.7 Graph principles 63 3.8 Issues with graphs 64 3.9 Pictogram principles 79 3.10 Comparative charts: Multiple pies, multiple bar charts, double scale graphs 82 3.11 Graphics 88 3.12 Three-dimensional charts 90 Notes 92 4 Numbers in text 93 4.1 Numbers written as text 94 4.1.1 Correct numbers 94 4.1.2 Clear numbers 94 4.1.3 Concise numbers 95 4.1.4 Consistent numbers 96 4.2 Ordering of data 97 4.3 Technical terms 98 4.4 Plain language 100 4.5 Emotive language 102 4.6 Key messages 103 Notes 105 5 Data presentation on the Internet 107 5.1 The early years 110 5.2 Statistics on CD-ROMs 113 5.3 Data on the Internet 116 5.4 Charts on the Internet 120 5.5 Text on the Internet 128 Notes 130

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Book SynopsisA valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data. Adding to the value in the new edition is: Illustrations of the use of R software to perform all the analyses in the book A new chapter on alternative methods for categorical data, including smoothing and regularization methods (such as the lasso), classification methods such as linear discriminant analysis and classification trees, and cluster analysis New sections in many chapters introducing the Bayesian approach for the methodTable of ContentsPreface ix About the Companion Website xiii 1 Introduction 1 1.1 Categorical Response Data 1 1.2 Probability Distributions for Categorical Data 3 1.3 Statistical Inference for a Proportion 5 1.4 Statistical Inference for Discrete Data 10 1.5 Bayesian Inference for Proportions * 13 1.6 Using R Software for Statistical Inference about Proportions * 17 Exercises 21 2 Analyzing Contingency Tables 25 2.1 Probability Structure for Contingency Tables 26 2.2 Comparing Proportions in 2 × 2 Contingency Tables 29 2.3 The Odds Ratio 31 2.4 Chi-Squared Tests of Independence 36 2.5 Testing Independence for Ordinal Variables 42 2.6 Exact Frequentist and Bayesian Inference * 46 2.7 Association in Three-Way Tables 52 Exercises 56 3 Generalized Linear Models 65 3.1 Components of a Generalized Linear Model 66 3.2 Generalized Linear Models for Binary Data 68 3.3 Generalized Linear Models for Counts and Rates 72 3.4 Statistical Inference and Model Checking 76 3.5 Fitting Generalized Linear Models 82 Exercises 84 4 Logistic Regression 89 4.1 The Logistic Regression Model 89 4.2 Statistical Inference for Logistic Regression 94 4.3 Logistic Regression with Categorical Predictors 98 4.4 Multiple Logistic Regression 102 4.5 Summarizing Effects in Logistic Regression 107 4.6 Summarizing Predictive Power: Classification Tables, ROC Curves, and Multiple Correlation 110 Exercises 113 5 Building and Applying Logistic Regression Models 123 5.1 Strategies in Model Selection 123 5.2 Model Checking 130 5.3 Infinite Estimates in Logistic Regression 136 5.4 Bayesian Inference, Penalized Likelihood, and Conditional Likelihood for Logistic Regression * 140 5.5 Alternative Link Functions: Linear Probability and Probit Models * 145 5.6 Sample Size and Power for Logistic Regression * 150 Exercises 151 6 Multicategory Logit Models 159 6.1 Baseline-Category Logit Models for Nominal Responses 159 6.2 Cumulative Logit Models for Ordinal Responses 167 6.3 Cumulative Link Models: Model Checking and Extensions * 176 6.4 Paired-Category Logit Modeling of Ordinal Responses * 184 Exercises 187 7 Loglinear Models for Contingency Tables and Counts 193 7.1 Loglinear Models for Counts in Contingency Tables 194 7.2 Statistical Inference for Loglinear Models 200 7.3 The Loglinear – Logistic Model Connection 207 7.4 Independence Graphs and Collapsibility 210 7.5 Modeling Ordinal Associations in Contingency Tables 214 7.6 Loglinear Modeling of Count Response Variables * 217 Exercises 221 8 Models for Matched Pairs 227 8.1 Comparing Dependent Proportions for Binary Matched Pairs 228 8.2 Marginal Models and Subject-Specific Models for Matched Pairs 230 8.3 Comparing Proportions for Nominal Matched-Pairs Responses 235 8.4 Comparing Proportions for Ordinal Matched-Pairs Responses 239 8.5 Analyzing Rater Agreement * 243 8.6 Bradley–Terry Model for Paired Preferences * 247 Exercises 249 9 Marginal Modeling of Correlated, Clustered Responses 253 9.1 Marginal Models Versus Subject-Specific Models 254 9.2 Marginal Modeling: The Generalized Estimating Equations (GEE) Approach 255 9.3 Marginal Modeling for Clustered Multinomial Responses 260 9.4 Transitional Modeling, Given the Past 263 9.5 Dealing with Missing Data * 266 Exercises 268 10 Random Effects: Generalized Linear Mixed Models 273 10.1 Random Effects Modeling of Clustered Categorical Data 273 10.2 Examples: Random Effects Models for Binary Data 278 10.3 Extensions to Multinomial Responses and Multiple Random Effect Terms 284 10.4 Multilevel (Hierarchical) Models 288 10.5 Latent Class Models * 291 Exercises 295 11 Classification and Smoothing * 299 11.1 Classification: Linear Discriminant Analysis 300 11.2 Classification: Tree-Based Prediction 302 11.3 Cluster Analysis for Categorical Responses 306 11.4 Smoothing: Generalized Additive Models 310 11.5 Regularization for High-Dimensional Categorical Data (Large p) 313 Exercises 321 12 A Historical Tour of Categorical Data Analysis * 325 Appendix: Software for Categorical Data Analysis 331 A.1 R for Categorical Data Analysis 331 A.2 SAS for Categorical Data Analysis 332 A.3 Stata for Categorical Data Analysis 342 A.4 SPSS for Categorical Data Analysis 346 Brief Solutions to Odd-Numbered Exercises 349 Bibliography 363 Examples Index 365 Subject Index 369

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Book SynopsisLearn how to easily transform your data into engaging, interactive visual reports! Data is no longer the sole domain of tech professionals and scientists. Whether in our personal, business, or community lives, data is rapidly increasing in both importance and sheer volume. The ability to visualize all kinds of data is now within reach for anyone with a computer and an internet connection. Google Data Studio, quickly becoming the most popular free tool in data visualization, offers users a flexible, powerful way to transform private and public data into interactive knowledge that can be easily shared and understood. Hands On With Google Data Studio teaches you how to visualize your data today and produce professional quality results quickly and easily. No previous experience is required to get started right awayall you need is this guide, a Gmail account, and a little curiosity to access and visualize data just like large businesses and organizationTable of ContentsIntroduction xv Part I Data Studio Basics 1 Chapter 1 Data Studio and the Data Citizen 3 Data, Data Everywhere 4 Accessibility of Data 4 Deriving Value from Data 5 The Role of Data Studio 7 A Brief History of Data Studio 9 Fundamentals First 12 Where to Go for Help 12 Time to Get Started! 13 Chapter 2 Cooking with Google Data Studio 15 Our First Example 15 Step 1. Select a Dish to Prepare: Visualizing a Bank Account 16 Before We Start: Things You’ll Need 19 Step 2. Let’s Go Shopping! Getting the Data 19 Step 3. Unpack the Groceries: Setting Up Google Drive 21 Step 4. Preparing the Ingredients: Working with Google Sheets 22 Step 5. Familiarizing Yourself with the Kitchen: Data Studio Home Screen and Starting a New Report 25 Step 6. Assemble the Ingredients: Connecting the Data to the Report 28 Step 7. Set the Table: Adding Your First Chart 35 Step 8. Keep Score with Scorecards 40 Step 9. It’s About Time: Building the Time-Series Chart 45 Step 10. Serving Suggestions: Finishing Touches and Sharing Your Report 50 Summary 55 Chapter 3 Enhancing Basic Graphs 57 Static Report Design 57 Before Getting Started: Things You’ll Need 59 Step 1. Copy the Report 60 Step 2. Modify the Header and Set the Date Range 61 Step 3. Modify Scorecards 63 Step 4. Modify Time-Series Chart 65 Step 5. Modify the Transactions Table 66 Step 6. Save the Report as PDF for Sharing 69 Summary 70 Chapter 4 Data Exploration with Interactive Elements 73 Building Our Workbench Example 73 Step 1. Selecting a Dish to Prepare: Exploration Workbench for a Bank Account 74 Step 2. Let’s Go Shopping! Getting the Data Set 77 Step 3. Assembling the Ingredients: Connecting Data to the Report 78 Adding Chart Components and Graphic Elements 82 Step 4. Reuse, Recycle, and Repurpose: Copying Elements from Other Reports 82 Step 5. Easy as Pie! Adding a Pie Chart 84 Step 6. Step Up to the Bar: Adding the Bar Chart 85 Step 7. Lining Things Up: Adding the Line Chart 90 Step 8. Tables, Again!? Setting Up the Table 91 Adding and Configuring Filter Controls 92 Step 9. Fun with Filters: Setting Up the Standard Filter Controls 92 Tips for Using Interactive Filters 94 Find the Answers: Filter Challenge 95 Summary 97 Part II Business and Marketing Applications 99 Chapter 5 Web Data Visualization with Google Analytics 101 Google Services for Websites and Business 102 A Brief Primer for Google Analytics 104 Using a Template to Create a New Report 106 Building the Google Analytics Report 110 Modifying the Charts 112 Working with the New Report 117 A Real-World Example: The Effects of a Beach Party in Spain on Web Traffic 117 The Limits of Demographic Data from Google Analytics 124 Now for a Side Dish: Adding a Page and Using Filters 126 Summary 132 Chapter 6 Using Google Search Console for Audience Insights 135 Search Console and Search Results Pages 136 Creating a Search Console Report with Data Studio 141 Step 1. Selecting the Dish to Prepare 142 Step 2. Let’s Go Shopping! 144 Step 3. Assemble the Ingredients 147 Step 4. Setting the Table 153 Bon Appetite! Using the Search Console Report 157 An Example for Your Soul! 161 Summary 170 Chapter 7 Viewing Local Organization Data from Google My Business 173 Google Search and the Local Organization 173 GMB: The New Home Page in the Search Results 175 What the User Sees in a GMB Listing 176 What the Owner Sees in a GMB Listing 180 Why Use Data Studio for GMB? 185 Step 1. Selecting the Dish to Prepare 187 The Actions Page 189 The Reviews Page 190 The Search Page 192 Before You Begin: What You Need to Get Started 194 Step 2. Let’s Go Shopping and Assemble the Ingredients 195 Step 3. Setting the Table 202 Report, Page, and Header Setup 203 Page Navigation Button Setup 206 Building the Actions Page 209 Building the Search Page 213 Building the Reviews Page 215 Summary 218 Part III Beyond the Office 221 Chapter 8 Getting Personal 223 Creating Your Own Data 223 Using Google Forms to Collect Your Own Data 225 Curating Data from Other Sources 248 Setting Up IFTTT to Capture Tweets 250 Preparing the Google Sheet for Data Studio 256 Create a Data Source for the Google Sheet 256 Create the New Twitter Report 258 Working with Data Generated for You 262 Music Service Tracking Example 262 Google Fit Community Connector Example 269 Community Connector Setup for Google Fit 270 Bringing It All Together 280 Created Data 280 Curated Data 283 Generated Data 284 Summary 288 Chapter 9 Going Public 291 Shared Data Sets 291 Searching for Data Sets 292 Getting Data from Kaggle 294 Using a Kaggle Account 294 Building the UFO Sightings Workbench 302 Dealing with Performance Issues in Reports 307 Using the Extract Data Connector to Speed Up Reports 307 data.world and Makeover Monday 314 Bringing It Home: Real Estate in Your Neighborhood 330 Selecting the Dish to Prepare 331 Going Shopping: Hunting for Housing Data 332 Unpacking the Groceries: Moving the File to Google Drive 337 Preparing the Ingredients: Fixing Data Formatting Issues 338 Assembling the Ingredients: Connecting the Data to the Report 340 Preparing the Meal: The Plan Meets Reality 340 Sharing Your Dish: Embedding Reports 346 Embedding a Report in a Google Site 351 Embedding a Report in a WordPress Site 353 Dealing with Pivoted Data 356 Summary 361 Chapter 10 Where Do You Go from Here? 363 Helping Your Audience See the Light 363 Annotation Ideas for Static Reports 364 Annotation Ideas for Interactive Reports 367 Providing Detailed Instructions for Users 371 Community Visualizations 375 Data Studio as an Application Development Platform 377 Exotic Ingredients and Your Pantry 383 Data Blending 383 File Upload 388 BigQuery for Big Data 390 Community Connectors 395 The Latest Dishes: New Developments and Releases 396 Summary 396 Index 399

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Book SynopsisOrganize, plan, and build an exceptional data analytics team within your organization In Minding the Machines: Building and Leading Data Science and Analytics Teams, AI and analytics strategy expert Jeremy Adamson delivers an accessible and insightful roadmap to structuring and leading a successful analytics team. The book explores the tasks, strategies, methods, and frameworks necessary for an organization beginning their first foray into the analytics space or one that is rebooting its team for the umpteenth time in search of success. In this book, you'll discover: A focus on the three pillars of strategy, process, and people and their role in the iterative and ongoing effort of building an analytics teamRepeated emphasis on three guiding principles followed by successful analytics teams: start early, go slow, and fully commitThe importance of creating clear goals and objectives when creating a new analytics unit in an organization Perfect for executives, managers, team leads, and other business leaders tasked with structuring and leading a successful analytics team, Minding the Machines is also an indispensable resource for data scientists and analysts who seek to better understand how their individual efforts fit into their team's overall results.Table of ContentsForeword xiii Introduction xvi Chapter 1 Prologue 1 For the Leader from the Business 5 For the Career Transitioner 6 For the Motivated Practitioner 6 For the Student 7 For the Analytics Leader 8 Structure of This Book 8 Why is This Book Needed? 9 Communication Gap 9 Troubles with Taylorism 10 Rinse, Report, Repeat 12 Too Fast, Too Slow 13 More Data, More Problems 14 Summary 15 Chapter 2 Strategy 17 The Role of Analytics in the Organization 20 The Analytics Playbook 20 Data and Analytics as a Culture Change 24 Current State Assessment 26 Readiness Assessment 26 Capability Modeling and Mapping 28 Technology Stack Review 32 Data Quality and Governance 34 Stakeholder Engagement 35 Defining the Future State 37 Defining the Mandate 39 Analytics Governance Model 40 Target Operating Model 42 Define Your Principles 43 Functions, Services, and Capabilities 43 Interaction Models 44 Organizational Design 48 Community of Practice 52 Project Delivery Model 55 Closing the Gap 57 Setting the Horizon 58 Establishing a Talent Roadmap 59 Consultants and Contractors 60 Change Management 62 Implementing Governance Models 64 Summary 65 Chapter 3 Process 69 Project Planning 73 Intake and Prioritization 73 Project Pipelines 77 Portfolio Project Management 80 Project Scoping and Planning 83 Scoping and Requirements Definition 86 Planning 92 Project Execution 96 Governance Structure and Communication Plan 99 Project Kickoff 102 Agile Analytics 103 Change and Stakeholder Management 106 Skeuomorphs 106 AI 101 and Project Brainstorming 107 Iterative Insights 110 Closeout and Delivery 111 Automation 112 Project Debrief 114 Summary 118 Chapter 4 People 121 Building the Team 122 Success Factors 123 Team Composition 128 Hiring and Onboarding 129 Talent Development 131 Retention 136 Departures 137 The Data Scientist Hierarchy of Needs 139 Culture 140 Innovation 145 Communication 147 Succession Planning 149 Potential Pitfalls 151 Dunning-Kruger Effect 152 Diderot Effect 153 Leading the Team 154 Data Scientists as Craftspeople 157 Team Conventions 160 Formal Meetings 162 Coffee Chats 164 Managing Conflict 167 Relationship Management 169 Owning the Narrative 175 Performance Metrics 177 Summary 181 Chapter 5 Future of Business Analytics 187 AutoML and the No‐Code Movement 189 Data Science is Dead 192 The Data Warehouse 195 True Operationalization 196 Exogenous Data 198 Edge AI 199 Analytics for Good 200 Analytics for Evil 201 Ethics and Bias 203 Analytics Talent Shortages 204 Death of the Career Transitioner 206 Chapter 6 Summary 211 Chapter 7 Coda 213 Index 215

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Book SynopsisTable of ContentsAcknowledgment xi Preface xiii 1 Data Munging Basics 1 Introduction 1 1.1 Filtering and Selecting Data 6 1.2 Treating Missing Values 11 1.3 Removing Duplicates 14 1.4 Concatenating and Transforming Data 16 1.5 Grouping and Data Aggregation 20 References 20 2 Data Visualization 23 2.1 Creating Standard Plots (Line, Bar, Pie) 26 2.2 Defining Elements of a Plot 30 2.3 Plot Formatting 33 2.4 Creating Labels and Annotations 38 2.5 Creating Visualizations from Time Series Data 42 2.6 Constructing Histograms, Box Plots, and Scatter Plots 44 References 54 3 Basic Math and Statistics 57 3.1 Linear Algebra 57 3.2 Calculus 58 3.2.1 Differential Calculus 58 3.2.2 Integral Calculus 58 3.3 Inferential Statistics 60 3.3.1 Central Limit Theorem 60 3.3.2 Hypothesis Testing 60 3.3.3 ANOVA 60 3.3.4 Qualitative Data Analysis 60 3.4 Using NumPy to Perform Arithmetic Operations on Data 61 3.5 Generating Summary Statistics Using Pandas and Scipy 64 3.6 Summarizing Categorical Data Using Pandas 68 3.7 Starting with Parametric Methods in Pandas and Scipy 84 3.8 Delving Into Non-Parametric Methods Using Pandas and Scipy 87 3.9 Transforming Dataset Distributions 91 References 94 4 Introduction to Machine Learning 97 4.1 Introduction to Machine Learning 97 4.2 Types of Machine Learning Algorithms 101 4.3 Explanatory Factor Analysis 114 4.4 Principal Component Analysis (PCA) 115 References 121 5 Outlier Analysis 123 5.1 Extreme Value Analysis Using Univariate Methods 123 5.2 Multivariate Analysis for Outlier Detection 125 5.3 DBSCan Clustering to Identify Outliers 127 References 133 6 Cluster Analysis 135 6.1 K-Means Algorithm 135 6.2 Hierarchial Methods 141 6.3 Instance-Based Learning w/ k-Nearest Neighbor 149 References 156 7 Network Analysis with NetworkX 157 7.1 Working with Graph Objects 159 7.2 Simulating a Social Network (ie; Directed Network Analysis) 163 7.3 Analyzing a Social Network 169 References 171 8 Basic Algorithmic Learning 173 8.1 Linear Regression 173 8.2 Logistic Regression 183 8.3 Naive Bayes Classifiers 189 References 195 9 Web-Based Data Visualizations with Plotly 197 9.1 Collaborative Aanalytics 197 9.2 Basic Charts 208 9.3 Statistical Charts 212 9.4 Plotly Maps 216 References 219 10 Web Scraping with Beautiful Soup 221 10.1 The BeautifulSoup Object 224 10.2 Exploring NavigableString Objects 228 10.3 Data Parsing 230 10.4 Web Scraping 233 10.5 Ensemble Models with Random Forests 235 References 254 Data Science Projects 257 11 Covid19 Detection and Prediction 259 Bibliography 275 12 Leaf Disease Detection 277 Bibliography 283 13 Brain Tumor Detection with Data Science 285 Bibliography 295 14 Color Detection with Python 297 Bibliography 300 15 Detecting Parkinson’s Disease 301 Bibliography 302 16 Sentiment Analysis 303 Bibliography 306 17 Road Lane Line Detection 307 Bibliography 315 18 Fake News Detection 317 Bibliography 318 19 Speech Emotion Recognition 319 Bibliography 322 20 Gender and Age Detection with Data Science 323 Bibliography 339 21 Diabetic Retinopathy 341 Bibliography 350 22 Driver Drowsiness Detection in Python 351 Bibliography 356 23 Chatbot Using Python 357 Bibliography 363 24 Handwritten Digit Recognition Project 365 Bibliography 368 25 Image Caption Generator Project in Python 369 Bibliography 379 26 Credit Card Fraud Detection Project 381 Bibliography 391 27 Movie Recommendation System 393 Bibliography 411 28 Customer Segmentation 413 Bibliography 431 29 Breast Cancer Classification 433 Bibliography 443 30 Traffic Signs Recognition 445 Bibliography 453

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Book SynopsisCritical Theory and Qualitative Data Analysis in Education offers a path-breaking explanation of how critical theories can be used within the analysis of qualitative data to inform research processes, such as data collection, analysis, and interpretation. This contributed volume offers examples of qualitative data analysis techniques and exemplars of empirical studies that employ critical theory concepts in data analysis. By creating a clear and accessible bridge between data analysis and critical social theories, this book helps scholars and researchers effectively translate their research designs and findings to multiple audiences for more equitable outcomes and disruption of historical and contemporary inequality.Trade Review"In addition to offering ways for scholars to build on existing methodologies, contributors to this volume also offer new paradigms while inviting all scholars to consider their tools…. I am encouraged by education researchers desire to transcend contrived borders and employ the methods, forms of methods, analysis, and strategic reconstruction of these forms in order to ask an entirely new set of questions."—from the Foreword by Maisha T. Winn, Chancellor's Leadership Professor, and Co-Director of Transformative Justice in Education (TJE) at the University of California- Davis, USAThis book provides critical scholars interested in paying attention to the larger social structural issues and oppression with tangible "how to’s" for critical qualitative data analysis and, in this way, encourage researchers to work toward social change. Too often data analysis processes are reductive and void of theory and, importantly, the authors fill a gap in the existing literature. This thoughtful book is useful for introductory qualitative researchers and senior scholars alike. — Penny A. Pasque, Professor and Department Head, Educational Leadership, Policy, and Human Development, North Carolina State University, USATable of ContentsContentsForeword: Reflections on Research that is Humanizing Maisha T. WinnPreface Ashley N. Gaskew, Jamile Lee-Johnson, and Rachelle Winkle-WagnerSection I The Need for Partnering Critical Theory and Data Analysis in EducationChapter 1 The Missing Link in Data Analysis: An Introduction to the Use of Critical Theory to Guide Data Analysis Rachelle Winkle-Wagner, Ashley Gaskew, and Jamila Lee-JohnsonChapter 2 The Missing InfinitePhil Frances CarspeckenChapter 3 Trouble the Translating: Border Thinking, Indigenous Knowledges, and Undoing MethodNathaniel BeckChapter 4 De-Norming the Syllabus: An Analysis Situated in Critical and Caring PedagogiesVirginia M. Schwarz Section II Critical Theory and Analysis with Marginalized Populations Section Introduction Keon M. McGuire Chapter 5 Illuminating Systemic Inequality in Educations: Using Bourdieu in Critical Qualitative Data AnalysisTangela Blakely Reavis Chapter 6 "Wanna Be Startnin’ Somethin:" Answering the Methodological "Call" To Position Complex Blackness in Conversation with Hermeneutic PhenomenologySteve D. Mobley, Jr. Chapter 7 Thinking with Queer of Color Critique: A Multidimensional Approach to Analyzing and Interpreting DataReginald A. Blockett Chapter 8 Globalization, Higher Education, and Crisis: A Model for Applying Critical Geography toward Data AnalysisChelsea A. Blackburn CohenChapter 9 Context and Materiality: Inclusive Appropriations of New Materialism for Qualitative AnalysisBarbara Dennis Section III Critical Theories and Data Analysis in Institutions and Policies Section IntroductionChristina W. Yao Chapter 10 A Culture of Values: Rethinking School Quality and Culture through Fanonian Critical TheoryJacqueline M. ForbesChapter 11 Discourse, Representation, and "Othering": Postcolonial Analysis of Donald Trump’s Education ReformMercy AgyepongChapter 12 Analyzing Policy Critically: Using Critical Race Theory to AnalyzeRachelle Winkle-Wagner, Thandi Sulè, and Dina C. Maramba Chapter 13 Habermas and Data Analysis in For-Profit Higher Education InstitutionsAshley GaskewChapter 14 Sistahs’ are Doin’ it for themselves: Using Social Media to (Re)Center Black Women’s Voices in Educational ResearchJamila Lee-Johnson and Lora HendersonAfterwordJamila Lee-Johnson, Ashley Gaskew, and Rachelle Winkle-WagnerContributor Bios

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Book SynopsisThe construction industry is vital to any national economy; it is also one of the industries most susceptible to workplace incidents. The unacceptably high rates of incidents in construction have huge socio-economic consequences for the victims, their families and friends, co-workers, employers and society at large. Construction safety researchers have introduced numerous strategies, models and tools through scientific inquiries involving primary data collection and analyses. While these efforts are commendable, there is a huge potential to create new knowledge and predictive models to improve construction safety by utilising already existing data about workplace incidents. In this new book, Imriyas Kamardeen argues that more sophisticated approaches need to be deployed to enable improved analyses of incident data sets and the extraction of more valuable insights, patterns and knowledge to prevent work injuries and illnesses.The book aims to apply data mining and analytic tecTable of ContentsPreface iAcknowledgements iiFigures iiiTables vAbbreviations vi Introduction Curtailing construction fatalities using analytics Reducing uncertainties in compensation for occupational diseases in construction using analytics Curbing psychological injuries in construction using analytics Predicting and preventing secondary psychological injuries in construction using analytics Conclusion Index

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Book SynopsisThis book presents an accessible introduction to data-driven storytelling. Resulting from unique discussions between data visualization researchers and data journalists, it offers an integrated definition of the topic, presents vivid examples and patterns for data storytelling, and calls out key challenges and new opportunities for researchers and practitioners.  Trade ReviewTrumpets please! This lucidly written report on data-driven storytelling lays out the compelling benefits and substantial challenges of this potent journalistic innovation. The strong team of authors offer fresh thinking and thoughtful guidance on exploration, explanation, engagement, ethics, and evaluation. Packed with examples for practitioners and references for researchers, this book opens up fresh possibilities that extend information visualization into decision-making, policy-shifting, and mind-changing applications.--Ben Shneiderman, University of MarylandData-Driven Storytelling presents an accessible and informative introduction to data-driven storytelling. Resulting from unique discussions between data visualization researchers and data journalists, Data-Driven Storytelling offers an integrated definition of the topic, presents vivid examples and patterns for data storytelling, and calls out key challenges and new opportunities for researchers and practitioners. The newest addition to the simply outstanding CRC Press 'A K Peters Visualization Series', Data-Driven Storytelling is unreservedly recommended for professional, corporate, college, and university library Computer Science & Engineering collections and supplemental studies reading lists.--Midwest Book Review, May 2018 Data-Driven Storytelling promotes an efficient way of data-driven storytelling in professionalism and its profound implications. This approach involves visualizations, explorations, explanations, curated visuals, narrative design patterns, process from analysis to communication, impressing the audience, ethical guidelines and evaluation methods on successful the data driven storytelling.--Ramalingam Shanmugam, Journal of Statistical Computation and Simulation“This bible of data-driven storytelling covers everything you need to know about the topic, from storytelling techniques (including scrollytelling) and narrative design patterns to evaluation and ethics in storytelling, providing readers with explanations and examples of the concepts described as well as extensive reference material. All of this is expressed in an accurate, concise, and clear way.”--Lorenzo Amabili, University of Groningen, Book Review in NightingaleTrumpets please! This lucidly written report on data-driven storytelling lays out the compelling benefits and substantial challenges of this potent journalistic innovation. The strong team of authors offer fresh thinking and thoughtful guidance on exploration, explanation, engagement, ethics, and evaluation. Packed with examples for practitioners and references for researchers, this book opens up fresh possibilities that extend information visualization into decision-making, policy-shifting, and mind-changing applications.--Ben Shneiderman, University of MarylandData-Driven Storytelling presents an accessible and informative introduction to data-driven storytelling. Resulting from unique discussions between data visualization researchers and data journalists, Data-Driven Storytelling offers an integrated definition of the topic, presents vivid examples and patterns for data storytelling, and calls out key challenges and new opportunities for researchers and practitioners. The newest addition to the simply outstanding CRC Press 'A K Peters Visualization Series', Data-Driven Storytelling is unreservedly recommended for professional, corporate, college, and university library Computer Science & Engineering collections and supplemental studies reading lists.--Midwest Book Review, May 2018 Data-Driven Storytelling promotes an efficient way of data-driven storytelling in professionalism and its profound implications. This approach involves visualizations, explorations, explanations, curated visuals, narrative design patterns, process from analysis to communication, impressing the audience, ethical guidelines and evaluation methods on successful the data driven storytelling.--Ramalingam Shanmugam, Journal of Statistical Computation and Simulation“This bible of data-driven storytelling covers everything you need to know about the topic, from storytelling techniques (including scrollytelling) and narrative design patterns to evaluation and ethics in storytelling, providing readers with explanations and examples of the concepts described as well as extensive reference material. All of this is expressed in an accurate, concise, and clear way.”--Lorenzo Amabili, University of Groningen, Book Review in NightingaleTable of ContentsIntroduction. From Cognitive to Design Principles. Exploration and Explanation in Data-Driven Storytelling. Data-Driven Storytelling Techniques: Analysis of a Curated Collection of Visual Stories. Narrative Design Patterns for Data-Driven Storytelling. Watches to Augmented Reality Devices and Gadgets for Data-Driven Storytelling. From Analysis to Communication Supporting the Lifecycle of a Story. Organizing the Work of Data-Driven Visual Storytelling. Communicating Data to an Audience.Ethics in Data-Driven Visual Storytelling. Evaluating Data-Driven Stories & Storytelling Tools.

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Book SynopsisMichael Barrow is an Honorary Senior Lecturer in Economics at the University of Sussex, where he has taught economics, statistics and quantitative methods, as well as conducted research in the field of public economics. He continues his consultancy work for the UK government and other voluntary activities. C. Rashaad Shabab is an award-winning teacher at the University of Sussex. He is a Senior Lecturer in Economics and the Business School's Director of Student Experience. He holds a PhD in Economics, specialising in household inequality, income risk, lifecycle theory and migration.

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Book SynopsisWhat happens to risk as the economic horizon goes to zero and risk is seen as an exposure to a change in state that may occur instantaneously at any time? All activities that have been undertaken statically at a fixed finite horizon can now be reconsidered dynamically at a zero time horizon, with arrival rates at the core of the modeling. This book, aimed at practitioners and researchers in financial risk, delivers the theoretical framework and various applications of the newly established dynamic conic finance theory. The result is a nonlinear non-Gaussian valuation framework for risk management in finance. Risk-free assets disappear and low risk portfolios must pay for their risk reduction with negative expected returns. Hedges may be constructed to enhance value by exploiting risk interactions. Dynamic trading mechanisms are synthesized by machine learning algorithms. Optimal exposures are designed for option positioning simultaneously across all strikes and maturities.Table of Contents1. Introduction; 2. Univariate risk representation using arrival rates; 3. Estimation of univariate arrival rates from time series data; 4. Estimation of univariate arrival rates from option surface data; 5. Multivariate arrival rates associated with prespecified univariate arrival rates; 6. The measure-distorted valuation as a financial objective; 7. Representing market realities; 8. Measure-distorted value-maximizing hedges in practice; 9. Conic hedging contributions and comparisons; 10. Designing optimal univariate exposures; 11. Multivariate static hedge designs using measure-distorted valuations; 12. Static portfolio allocation theory for measure-distorted valuations; 13. Dynamic valuation via nonlinear martingales and associated backward stochastic partial integro-differential equations; 14. Dynamic portfolio theory; 15. Enterprise valuation using infinite and finite horizon valuation of terminal liquidation; 16. Economic acceptability; 17. Trading Markovian models; 18. Market implied measure-distortion parameters; References; Index.

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Book SynopsisThis concise book for scientists and students interested in bioinformatics and data science covers all aspects of predictive modeling for biomarker discovery based on high-dimensional data, as well as modern data science methods for identification of parsimonious and robust multivariate biomarkers for medical diagnosis and personalized medicine.

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Book SynopsisOptimization techniques are at the core of data science, including data analysis and machine learning. An understanding of basic optimization techniques and their fundamental properties provides important grounding for students, researchers, and practitioners in these areas. This text covers the fundamentals of optimization algorithms in a compact, self-contained way, focusing on the techniques most relevant to data science. An introductory chapter demonstrates that many standard problems in data science can be formulated as optimization problems. Next, many fundamental methods in optimization are described and analyzed, including: gradient and accelerated gradient methods for unconstrained optimization of smooth (especially convex) functions; the stochastic gradient method, a workhorse algorithm in machine learning; the coordinate descent approach; several key algorithms for constrained optimization problems; algorithms for minimizing nonsmooth functions arising in data science; foundTrade Review'This delightful compact tome gives the reader all the results they should have in their pocket to contribute to optimization and statistical learning. With the clean, elegant derivations of many of the foundational optimization methods underlying modern large-scale data analysis, everyone from students just getting started to researchers knowing this book inside and out will be well-positioned for both using the algorithms and developing new ones for machine learning, optimization, and statistics.' John C. Duchi, Stanford University'Optimization algorithms play a vital role in the rapidly evolving field of machine learning, as well as in signal processing, statistics and control. Numerical optimization is a vast field, however, and a student wishing to learn the methods required in the world of data science could easily get lost in the literature. This book does a superb job of presenting the most important algorithms, providing both their mathematical foundations and lucid motivations for their development. Written by two of the foremost experts in the field, this book gently guides a reader without prior knowledge of optimization towards the methods and concepts that are central in modern data science applications.' Jorge Nocedal, Northwestern University'This timely introductory book gives a rigorous view of continuous optimization techniques which are being used in machine learning. It is an excellent resource for those who are interested in understanding the mathematical concepts behind commonly used machine learning techniques.' Shai Shalev-Shwartz, Hebrew University of Jerusalem'This textbook is a much-needed exposition of optimization techniques, presented with conciseness and precision, with emphasis on topics most relevant for data science and machine learning applications. I imagine that this book will be immensely popular in university courses across the globe, and become a standard reference used by researchers in the area.' Amitabh Basu, Johns Hopkins UniversityTable of Contents1. Introduction; 2. Foundations of smooth optimization; 3. Descent methods; 4. Gradient methods using momentum; 5. Stochastic gradient; 6. Coordinate descent; 7. First-order methods for constrained optimization; 8. Nonsmooth functions and subgradients; 9. Nonsmooth optimization methods; 10. Duality and algorithms; 11. Differentiation and adjoints.

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Book SynopsisHow can you carry out discourse analysis using corpus linguistics? What research questions should I ask? Which methods should you use and when? What is a collocational network or a key cluster? Introducing the major techniques, methods and tools for corpus-assisted analysis of discourse, this book answers these questions and more, showing readers how to best use corpora in their analyses of discourse. Using carefully tailored case studies, each chapter is devoted to a central technique, including frequency, concordancing and keywords, going step by step through the process of applying different analytical procedures. Introducing a wide range of different corpora, from holiday brochures to political debates, the book considers the key debates and latest advances in the field. Fully revised and updated, this new edition includes:- A new chapter on how to conduct research projects in corpus-based discourse analysis- Completely rewritten chapters on collocation and advanced techniTrade ReviewBaker (Lancaster University, UK) looks at how corpora (computerized collections of naturally occurring language samples) can be used for discourse analysis. The book has four particular strengths. First, the author explains corpus methodologies thoroughly, including frequency and dispersion, concordances, collocates, and keyness. Second, the grounds his explanations in concrete analyses of discourse used in tourism brochures, fox-hunting debates, and news articles on refugees (among other texts), thereby offering exemplars of the methodology; included are several tabular examples of analysis. And fourth, he explores the strengths and limitations of corpus analysis, explaining the need for self-reflection with respect to methodological decision-making. An excellent guide to the scope and method of corpus linguistics as applied to discourse analysis, this book on research methods will be valuable to those in linguistics, rhetoric and communication, literary theory and other humanities fields. * Choice Reviews (of the first edition) *Is a necessity for any researcher, practitioner or student interested in the interplay of content, discourse and corpus linguistics. It is a practical, hands-on guide that articulately explores the complex workings of corpora building and analysis. It is a valuable contribution for both the novice exploring the field and the more experienced scholar aiming to refresh their understanding of this ever-growing, ever-evolving discipline. * Discourse Studies (of the first edition) *Corpus methodologies have a huge potential for use in discourse studies, and Paul Baker has written a superb introduction that combines common sense and academic expertise. As a practical 'how-to' advisor he provides an accessible explanation of the key technical and interpretative issues. As an advocate of innovation, he is sensitive to the priorities and the research paradigms of both the discourse analyst and the corpus linguist. This is a splendid book that will inspire a new generation of research. -- Professor Susan Hunston, Department of English, University of Birmingham (of the first edition)We are given examples of research which demonstrate the various techniques and these can be intriguing...Using Corpora in Discourse Analysis should indeed build bridges, for those who are not already using them, but it will also be useful to anyone interested in language as it is used in texts...the generative nature of the techniques should be stimulating for all those who monitor language use... -- Alison Duguid * Times Literary Supplement (of the first edition) *If you want to know what corpus linguistics can offer to sociolinguists interested in the relationship between language and gender, this book is the answer. I found it hard to put down. Written in a wonderfully accessible style, it provides detailed examples of the challenging questions, messy data, and satisfying, though often approximate, answers that corpus linguistics can provide. It confronts researchers with the real nitty-gritty of the challenges and rewards of each step of a corpus linguistics project. Researchers and students will both find it invaluable. -- Janet Holmes, Professor of Linguistics, Victoria University of Wellington, New Zealand (of the first edition)One of the best introductory texts on corpus assisted discourse analysis currently available. Baker expertly embeds concrete examples of critical data analysis within wider discussion of methodological choices, using a range of corpus tools. Readers will find the step by step guides particularly useful, along with Baker’s inimitable clear and engaging writing style. -- Valerie Hobbs, Senior Lecturer in Applied Linguistics, University of Sheffield, UKThis new edition combines clear explanations of key corpus concepts with significantly updated chapters. Highlighted throughout are the technological advancements in corpus tools as they are applied to contemporary research questions. Once again, Baker’s extensive expertise provides an invaluable resource for integrating discourse and corpus methodologies in linguistic research. -- Tammy Gales, Associate Professor of Linguistics, Hofstra University, USATable of Contents1. Introduction 2. The First Stages 3. Corpus Building and Annotation 4. Frequency and Dispersion 5. Concordances 6. Collocates 7. Keyness 8. Beyond Collocation 9. What Comes Next? Bibliography Index

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Book SynopsisHow can you carry out discourse analysis using corpus linguistics? What research questions should I ask? Which methods should you use and when? What is a collocational network or a key cluster? Introducing the major techniques, methods and tools for corpus-assisted analysis of discourse, this book answers these questions and more, showing readers how to best use corpora in their analyses of discourse. Using carefully tailored case studies, each chapter is devoted to a central technique, including frequency, concordancing and keywords, going step by step through the process of applying different analytical procedures. Introducing a wide range of different corpora, from holiday brochures to political debates, the book considers the key debates and latest advances in the field. Fully revised and updated, this new edition includes:- A new chapter on how to conduct research projects in corpus-based discourse analysis- Completely rewritten chapters on collocation and advanced techniTrade ReviewBaker (Lancaster University, UK) looks at how corpora (computerized collections of naturally occurring language samples) can be used for discourse analysis. The book has four particular strengths. First, the author explains corpus methodologies thoroughly, including frequency and dispersion, concordances, collocates, and keyness. Second, the grounds his explanations in concrete analyses of discourse used in tourism brochures, fox-hunting debates, and news articles on refugees (among other texts), thereby offering exemplars of the methodology; included are several tabular examples of analysis. And fourth, he explores the strengths and limitations of corpus analysis, explaining the need for self-reflection with respect to methodological decision-making. An excellent guide to the scope and method of corpus linguistics as applied to discourse analysis, this book on research methods will be valuable to those in linguistics, rhetoric and communication, literary theory and other humanities fields. * Choice Reviews (of the first edition) *Is a necessity for any researcher, practitioner or student interested in the interplay of content, discourse and corpus linguistics. It is a practical, hands-on guide that articulately explores the complex workings of corpora building and analysis. It is a valuable contribution for both the novice exploring the field and the more experienced scholar aiming to refresh their understanding of this ever-growing, ever-evolving discipline. * Discourse Studies (of the first edition) *Corpus methodologies have a huge potential for use in discourse studies, and Paul Baker has written a superb introduction that combines common sense and academic expertise. As a practical 'how-to' advisor he provides an accessible explanation of the key technical and interpretative issues. As an advocate of innovation, he is sensitive to the priorities and the research paradigms of both the discourse analyst and the corpus linguist. This is a splendid book that will inspire a new generation of research. -- Professor Susan Hunston, Department of English, University of Birmingham (of the first edition)We are given examples of research which demonstrate the various techniques and these can be intriguing...Using Corpora in Discourse Analysis should indeed build bridges, for those who are not already using them, but it will also be useful to anyone interested in language as it is used in texts...the generative nature of the techniques should be stimulating for all those who monitor language use... -- Alison Duguid * Times Literary Supplement (of the first edition) *If you want to know what corpus linguistics can offer to sociolinguists interested in the relationship between language and gender, this book is the answer. I found it hard to put down. Written in a wonderfully accessible style, it provides detailed examples of the challenging questions, messy data, and satisfying, though often approximate, answers that corpus linguistics can provide. It confronts researchers with the real nitty-gritty of the challenges and rewards of each step of a corpus linguistics project. Researchers and students will both find it invaluable. -- Janet Holmes, Professor of Linguistics, Victoria University of Wellington, New Zealand (of the first edition)One of the best introductory texts on corpus assisted discourse analysis currently available. Baker expertly embeds concrete examples of critical data analysis within wider discussion of methodological choices, using a range of corpus tools. Readers will find the step by step guides particularly useful, along with Baker’s inimitable clear and engaging writing style. -- Valerie Hobbs, Senior Lecturer in Applied Linguistics, University of Sheffield, UKThis new edition combines clear explanations of key corpus concepts with significantly updated chapters. Highlighted throughout are the technological advancements in corpus tools as they are applied to contemporary research questions. Once again, Baker’s extensive expertise provides an invaluable resource for integrating discourse and corpus methodologies in linguistic research. -- Tammy Gales, Associate Professor of Linguistics, Hofstra University, USATable of Contents1. Introduction 2. The First Stages 3. Corpus Building and Annotation 4. Frequency and Dispersion 5. Concordances 6. Collocates 7. Keyness 8. Beyond Collocation 9. What Comes Next? Bibliography Index

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Book SynopsisKevin Guyan is an equality, diversity and inclusion (EDI) researcher based in Edinburgh, Scotland. He is currently Head of Knowledge and Research at Advance HE, a higher education agency that works to improve EDI for staff and students in universities and colleges in the UK.Trade ReviewKevin Guyan’s Queer Data, though not a quick read, is very comprehensible to an average reader and is absolutely chockablock with ways to understand how research is conducted and how it systematically discounts queer people (or counts us incorrectly, or codes us incorrectly, or…). If you ever do research on anything involving people—even something as minor as a brand-preference survey—you must read this, absolutely. But even the lay reader with no research aspirations will find so many ways to prove that their homophobic cousin Karen is just plain wrong. * Xtra Magazine *[T]he book does an admirable job explaining the finer points behind the complicated constructs of sexual orientation and gender identity (SOGI) and drawing attention to nuances that make it difficult to precisely measure micro-minorities ... the book is a welcome addition on a topic that currently lacks wide attention. Guyan poses provocative questions that practitioners should consider before embarking on research that focuses on sexual and gender minorities. * Science Magazine *An accessible read, Queer Data is a must-read to understand why reliable data is necessary to ensure the improvement of everyday LGBTQ+ people, policies, and activist causes. -- One of Gay Times' 10 Most Anticipated Books of 2022A brilliant study on how [data is collected] within the LGBTQ community... enlightening reading. * Publishing Scotland *Each of Queer Data’s sections provides thought-provoking debates and relevant dilemmas grounded in rigorous academic concepts and rich evidence from practice. In this sense, one of the book’s core strengths is how it intertwines complex scholarly ideas with concrete problems that practitioners and activists wrestle within their day-to-day work. * Harvard Educational Review *...Very comprehensible to an average reader and absolutely chockablock with ways to understand how research is conducted and how it systematically discounts queer people...If you ever do research on anything involving people—even something as minor as a brand-preference survey—you must read this, absolutely. But even the lay reader with no research aspirations will find so many ways to prove that their homophobic cousin Karen is just plain wrong. * Xtra Magazine *A refreshingly clear and practical take which cuts through turbulent discourse and offers a new way of looking at fixing inequalities and responding to threats facing the LGBTQI+ community. * Emma Roddick, Member of the Scottish Parliament (MSP) *Committed to the project of changing the world for the better for Queer People, this book critically analyses the need to include LGBTQ people in policymaking. It’s enormously readable, theoretically informed and supported by evidence. * Julie Fish, Director of the Centre for LGBTQ Research, De Montfort University, UK *A unique, powerful call to action. Guyan boldly points out how queer data is ignored, ‘straightwashed’ or corrupted. It offers a way forward to engage with queer data to shape our own lived experiences. Highly recommended! * Drew Dalton, Senior Lecturer in Sociology and Programme Leader MSc Inequality and Society, University of Sunderland, UK *Zooming in on lesbian, gay, bisexual, trans, and queer (LGBTQ) rights, the book illuminates how increased knowledge about queer identities proves essential as a tool for action, which impacts decision making related to resource allocation, changes to legislation, access to services, representation, and visibility. * International Feminist Journal of Politics *This book undeniably deserves a place on your shelf and is a ‘must have’ for anyone in the academic field. * Journal of Cultural Analysis and Social Change *Table of Contents1. Introduction PART ONE - COLLECTING QUEER DATA 2. A history of queer data collection 3. Queer data in the Equality Act 4. Queer collection methods 5. Censuses 6. International approaches to queer data collection SECTION TWO - ANALYSING QUEER DATA 7. Making sense of queer data 8. Intersectional analysis SECTION THREE - USING QUEER DATA 9. Maintenance of the status quo 10. Your place to speak 11. For political action 12. Conclusion

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Book SynopsisJennifer Edmond is Associate Professor of Trinity College Dublin and the co-director of the Trinity Center for Digital Humanities, Ireland. Jennifer also serves as President of the Board of Directors of the pan-European research infrastructure for the arts and humanities, DARIAH-EU and represents this body on the Open Science Policy Platform (OSPP), which supports the European Commission in developing and promoting Open Science policies. Nicola Horsley's qualitative research critiques the marginalisation of the social in various discourses and explores the dominance of scientific and technical knowledge as bases for policy and practice. Her co-authored book, Challenging the Politics of Early Intervention explores the scientific evidence base for early intervention policies.Jörg Lehmann is a post-doctoral research fellow at the Romanistic Seminar at Eberhard Karls University Tübingen, Germany. He has published two monographs on war literaTrade ReviewBy examining the much-hyped phenomenon of ‘big data’ through a humanist lens, the authors provide a rich account of the possibilities and limits. They focus on the importance of culture and context for understanding how data are imagined, collected, analysed and understood. * Sally Wyatt, Professor of Digital Cultures, Maastricht University, the Netherlands *Table of ContentsIntroduction Chapter 1: Data and Language Chapter 2: Data and Sensemaking Chapter 3: Data and Invisibility Chapter 4: Big Data and the Abyss of Aggregation Chapter 5: Data and Power Conclusion

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Book SynopsisDiscover how the explosions in data analytics, AI, and digital communication are benefiting sports and sports fans around the world In Sports and Technology Have The Power To Change The World: Driving Positive Change Through The Use of Data and AI, the Director of Microsoft Sports, Jon Flynn, delivers an insightful new take on the transformative power of sport and its ability to unite people, break down barriers, and generate positive change. The author explains the critical role that technology has played in growing the impact of sporting events and enabling social change while fostering community improvement. In the book, you'll explore many of the ways in which sports, enabled by new tech, have made significant contributions to society and promoted individual development, health, and wellbeing. You'll also find: Discussions of green technologies and climate and sustainability initiatives linked to sport, with a case study about the 2022 Beijing Winter OlympicsExplorations of the impact of advanced data analytics, with a case study focusing on the 2013 NBA Final matchup between the Miami Heat and the San Antonio SpursHow sport scientists are optimizing player performance Perfect for anyone interested in the intersection of sport, society, and technology, Sports and Technology Have The Power To Change The World is an easy to read and endlessly fascinating look at how the unique combination of athletics and tech makes the world a better place.

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Book SynopsisJan-Willem Middelburg is a Dutch entrepreneur and author with a passion for technology and innovation. He is the CEO and co-founder of Cybiant, a global technology that company that helps to create a more sustainable world through analytics, big data and automation. He is also President and Chief Examiner of the Enterprise Big Data Framework, an independent organization dedicated to upskilling individuals with expertise in Big Data. In partnership with APMG-International, the Enterprise Big Data Framework offers vendor-neutral certifications for individuals.Trade Review"The Enterprise Big Data Framework is relevant for everybody within an organisation engaged in driving maximum benefits from data. There is something for everybody; from the board considering governance and ethical behaviour to individuals within the organisation knowing where they fit and the value they can get from better use of their organisation's data. If you are considering a transformation project, this is an excellent guide for your project team." * Richard Pharro, CEO, The APM Group Limited *"If you are looking for a good guide to empower your knowledge on big data and to find a framework to help you on your big data journey, then this book is for you. From learning what big data is to defining a big data strategy, Jan-Willem has built a book to empower the learner on the topic of big data." * Jordan Morrow, Chief Strategy & Transformation Officer, DataPrime and Author of Be Data Literate *"This book is a master piece for those who are familiar and those who discover the world of data. It provides an "a la carte framework" starting with a (big) data strategy and the supporting aspects such as big data functions, architecture and algorithms. It covers in depth data platforms architectures, its management as well as data governance, data catalogue and all the required security considerations associated to the various data classifications. You will find details of data life cycle management, of various machine learning algorithms and an important chapter covering AI ethics when building and deploying sophisticated algorithms using data. The concepts covered in this book apply to on-premises and in the (public) cloud environments, making this book a must read." * Jean-Michel Coeur, APAC Technology Practice Lead, Data Analytics, Google Cloud *Table of Contents Section - ONE: Introduction to Big Data; Chapter - 01: Introduction to Big Data; Chapter - 02: The Big Data framework; Chapter - 03: Big Data strategy; Chapter - 04: Big Data architecture; Chapter - 05: Big Data algorithms; Chapter - 06: Big Data processes; Chapter - 07: Big Data functions; Chapter - 08: Artificial intelligence; Section - TWO: Enterprise Big Data analysis; Chapter - 09: Introduction to Big Data analysis; Chapter - 10: Defining the business objective; Chapter - 11: Data ingestion – importing and reading data sets; Chapter - 12: Data preparation – cleaning and wrangling data; Chapter - 13: Data analysis – model building; Chapter - 14: Data presentation; Section - THREE: Enterprise Big Data engineering; Chapter - 15: Introduction to Big Data engineering; Chapter - 16: Data modelling; Chapter - 17: Constructing the data lake; Chapter - 18: Building an enterprise Big Data warehouse; Chapter - 19: Design and structure of Big Data pipelines; Chapter - 20: Managing data pipelines; Chapter - 21: Cluster technology; Section - FOUR: enterprise Big Data algorithm design; Chapter - 22: Introduction to Big Data algorithm design; Chapter - 23: Algorithm design – fundamental concepts; Chapter - 24: Statistical machine learning algorithms; Chapter - 25: The data science roadmap; Chapter - 26: Programming languages 26 visualization and simple metrics; Chapter - 27: Advanced machine learning algorithms; Chapter - 28: Advanced machine learning classification algorithms; Chapter - 29: Technical communication and documentation; Section - FIVE: Enterprise Big Data architecture; Chapter - 30: Introduction to the Big Data architecture; Chapter - 31: Strength and resilience – the Big Data platform; Chapter - 32: Design principles for Big Data architecture; Chapter - 33: Big Data infrastructure; Chapter - 34: Big Data platforms; Chapter - 35: The Big Data application provider; Chapter - 36: System orchestration in Big Data

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Book SynopsisJan-Willem Middelburg is a Dutch entrepreneur and author with a passion for technology and innovation. He is the CEO and co-founder of Cybiant, a global technology that company that helps to create a more sustainable world through analytics, big data and automation. He is also President and Chief Examiner of the Enterprise Big Data Framework, an independent organization dedicated to upskilling individuals with expertise in Big Data. In partnership with APMG-International, the Enterprise Big Data Framework offers vendor-neutral certifications for individuals.Trade Review"The Enterprise Big Data Framework is relevant for everybody within an organisation engaged in driving maximum benefits from data. There is something for everybody; from the board considering governance and ethical behaviour to individuals within the organisation knowing where they fit and the value they can get from better use of their organisation's data. If you are considering a transformation project, this is an excellent guide for your project team." * Richard Pharro, CEO, The APM Group Limited *"If you are looking for a good guide to empower your knowledge on big data and to find a framework to help you on your big data journey, then this book is for you. From learning what big data is to defining a big data strategy, Jan-Willem has built a book to empower the learner on the topic of big data." * Jordan Morrow, Chief Strategy & Transformation Officer, DataPrime and Author of Be Data Literate *"This book is a master piece for those who are familiar and those who discover the world of data. It provides an "a la carte framework" starting with a (big) data strategy and the supporting aspects such as big data functions, architecture and algorithms. It covers in depth data platforms architectures, its management as well as data governance, data catalogue and all the required security considerations associated to the various data classifications. You will find details of data life cycle management, of various machine learning algorithms and an important chapter covering AI ethics when building and deploying sophisticated algorithms using data. The concepts covered in this book apply to on-premises and in the (public) cloud environments, making this book a must read." * Jean-Michel Coeur, APAC Technology Practice Lead, Data Analytics, Google Cloud *Table of Contents Section - ONE: Introduction to Big Data; Chapter - 01: Introduction to Big Data; Chapter - 02: The Big Data framework; Chapter - 03: Big Data strategy; Chapter - 04: Big Data architecture; Chapter - 05: Big Data algorithms; Chapter - 06: Big Data processes; Chapter - 07: Big Data functions; Chapter - 08: Artificial intelligence; Section - TWO: Enterprise Big Data analysis; Chapter - 09: Introduction to Big Data analysis; Chapter - 10: Defining the business objective; Chapter - 11: Data ingestion – importing and reading data sets; Chapter - 12: Data preparation – cleaning and wrangling data; Chapter - 13: Data analysis – model building; Chapter - 14: Data presentation; Section - THREE: Enterprise Big Data engineering; Chapter - 15: Introduction to Big Data engineering; Chapter - 16: Data modelling; Chapter - 17: Constructing the data lake; Chapter - 18: Building an enterprise Big Data warehouse; Chapter - 19: Design and structure of Big Data pipelines; Chapter - 20: Managing data pipelines; Chapter - 21: Cluster technology; Section - FOUR: enterprise Big Data algorithm design; Chapter - 22: Introduction to Big Data algorithm design; Chapter - 23: Algorithm design – fundamental concepts; Chapter - 24: Statistical machine learning algorithms; Chapter - 25: The data science roadmap; Chapter - 26: Programming languages 26 visualization and simple metrics; Chapter - 27: Advanced machine learning algorithms; Chapter - 28: Advanced machine learning classification algorithms; Chapter - 29: Technical communication and documentation; Section - FIVE: Enterprise Big Data architecture; Chapter - 30: Introduction to the Big Data architecture; Chapter - 31: Strength and resilience – the Big Data platform; Chapter - 32: Design principles for Big Data architecture; Chapter - 33: Big Data infrastructure; Chapter - 34: Big Data platforms; Chapter - 35: The Big Data application provider; Chapter - 36: System orchestration in Big Data

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Book SynopsisNicholas Kelly is a principal at G&K Consulting, based in Bonney Lake, Washington. He is a leader in analytics adoption having designed and developed dashboards for some of the world's largest companies, from global banks to Formula 1 teams. He is a frequent speaker at international conferences, has trained thousands of professionals in data visualization and analytics adoption and is the inventor of the Dashboard Wireframe KitTrade Review"Over the many years I have worked in data analytics the field has grown significantly. It's no longer enough to deliver accurate numbers and charts: we need to consider business value, governance, adoption, story-telling and even corporate culture. Nick Kelly's book covers all that ground and more." * Donald Farmer, Principle, Tree Hive Strategy *"Achieving real business impact with data goes far beyond technical considerations - you must focus on the human considerations. Through practical examples and real-world stories, Nick has crafted a book that will teach you to capitalize on the human side of data analytics and deliver business-changing results." * David Langer, Founder, Dave on Data *"If you are looking to build an analytic capability or wondering how to improve one, this book covers the why what and how in a down to earth narrative. If you want to fast track from lessons learned and get your program running from the get-go, read this book first." * Akihiko Katayama, Chief Technology Officer, BaronsAI *Table of Contents Chapter - 01: Insight mindset; Chapter - 02: Strategy and planning; Chapter - 03: UX principles; Chapter - 04: Requirements gathering; Chapter - 05: Data assessment; Chapter - 06: The agile process; Chapter - 07: Storytelling; Chapter - 08: Crafting the vision; Chapter - 09: Managing change; Chapter - 10: Adoption and ownership; Chapter - 11: Training and documentation; Chapter - 12: Launch

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Book SynopsisDr Antonio Weiss, based in London, UK, is a Senior Partner at The PSC, an award-winning public service consultancy specialising in user-centred design, digital, strategy and delivery. He has advised the Office for Artificial Intelligence, the UK Space Agency and NHSx as well as numerous other pioneering digital organizations and frequently trains leaders to become digital transformation experts. He is also an Affiliated Researcher at the University of Cambridge's Digital State programme and the co-founder of Thomas Clipper, an e-commerce lifestyle brand for men featured in GQ, The Guardian and The Telegraph.Trade Review"Refreshingly free of waffle and ego, this is an incredibly valuable guide - in fact almost a recipe - for launching and landing meaningful digital and business transformation. Every page shares precision insights and immediately actionable suggestions with a simplicity and clarity that only comes from many years of walking the walk. As useful for someone starting their digital transformation journey as one despairing about their progress to date!" * Pete Herlihy, Lead Product Manager, UK Government Digital Service *"This is a great book that will be of huge help to those involved in digitally enabled transformation. It is intensely practical, with many good case studies, but also very readable. The book is aimed squarely at those responsible for initiating and leading the change rather than technical experts. From me it comes strongly recommended. I wish it had been written a long time ago." * Lord Bob Kerslake, former Head of the UK Civil Service *"Digitalisation will have a major impact on the way services are provided and how business is conducted. Digital Transformation can seem like a daunting challenge to any business leader and it is essential that we all build our understanding and knowledge as these major changes take place. This excellent practical guide, written by Antonio Weiss will help you achieve this and de-risk your transformation programme. The guide gives you the tools and advice that you will need to succeed as well as being a valuable resource for those leading any digital change process." * Sir Ian Carruthers, Chancellor of the University of the West of England and former NHS Chief Executive *"Organizations globally are spending billions on digital transformation right now; for many, it is one of their very largest investment areas. But it is easy to waste money on technology, consulting and internal costs because organisations and leaders don't know what they are really trying to do, or how to achieve their goals. The Practical Guide to Digital Transformation is truly practical, with great examples, case studies and tips that will be of value to anyone tasked with delivery. I particularly liked the "what you might say in your next meeting" list at the end of each chapter, and this book is destined to become a well-used friend to many senior managers, consultants and business students." * Peter Smith, Procurement expert and author of Bad Buying *"Organisations are more aware than ever of the need to transform themselves for the digital age. But many, perhaps most, still struggle. The Practical Guide to Digital Transformation is the ideal companion for any company serious about adaptation. Written by a leading digital transformation expert, it provides the ideas and vocabulary to bring about change, illuminated by incisive case studies. It is written in user-friendly language, guiding the reader through the "whys" and "hows" of making change happen. This outstanding guide is essential reading for decision-makers, digital leaders, and practitioners seeking to ensure that their organisations thrive now and in the future." * Dr Tanya Filer, Digital State Project Lead, Bennett Institute for Public Policy, University of Cambridge and founder of StateUp *"The Practical Guide to Digital Transformation is a really excellent, step by step primer to help your organisation get the very best from digital technology. It is clear but not dumbed-down. It will expand the thinking of new and experienced digital leaders alike, and gives concrete, actionable ways of bringing your organisation with you." * Phil Buckley, Prix Jeunesse and BIMA award-winning Digital Product Manager *"This book provides a unique, pragmatic, real-world guide to digital transformation. Each chapter unlocks different aspects, viewpoints and the considerations needed to embed change in a multitude of environments. The book is pitched to all audiences, providing the tools needed for anyone interested or actively involved in digital transformation. Antonio has managed to pack the learning from his many years as a consultant into this wonderful book." * Gary McAllister, Chief Technology Officer for NHS London and author of An Introduction to Digital Healthcare in the NHS *"For anyone trying to implement transformative change in their organisation - this is a complete must have. It's a remarkably waffle-free book that shows how to put theory into practice in the most practical of ways - with real world examples of where it's worked and where it hasn't. It's genuinely a breath of fresh air and an invaluable read for anyone interested in using digital principles and tools to transform their organisation." * Tom Lillywhite, Director of Digital Transformation, UK Labour Party *Table of Contents Chapter - 00: Introduction; Section - ONE: Getting the strategy and the roadmap right; Chapter - 01: What is a digital strategy?; Chapter - 02: Choosing your strategic delivery vehicle; Chapter - 03: How to do a digital roadmap; Section - TWO: Making change happen; Chapter - 04: Ways of working; Chapter - 05: Senior and organisational buy-in; Chapter - 06: Funding digital; Section - THREE: Doing digital; Chapter - 07: Understanding your users; Chapter - 08: Doing the bare minimum; Chapter - 09: Building new services; Chapter - 10: Buying technology; Chapter - 11: The cloud, APIs and open-source; Chapter - 12: Using data science to inform decision-making; Chapter - 13: Stimulating innovation; Section - FOUR: Future-proofing; Chapter - 14: Protecting and defending your organisation; Chapter - 15: The ethical digital organisation; Chapter - 16: Upskilling and bringing in new talent; Chapter - 17: Defining the next horizon

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Book SynopsisJordan Morrow is known as the "Godfather of Data Literacy", having helped pioneer the field by building one of the world's first data literacy programs. He is the founder and CEO of Bodhi Data, served as the Chair of the Advisory Board for The Data Literacy Project and has helped companies and organizations around the world, including the United Nations, build and understand data literacy. Morrow is the author of three books: Be Data Literate, Be Data Driven, and Be Data Analytical, all published by Kogan Page. He is based near Salt Lake City, Utah.Trade Review"Jordan Morrow has done it again. This flows on perfectly from his first book, Be Data Literate, and creates a realistic and achievable pathway for organizations to become data driven. And, of course, at the center of it is people-a man after my own data heart! I hope that wasn't a spoiler alert..." * Susan Walsh, The Classification Guru and author of Between the Spreadsheets *"Understanding the basics of data science and AI is key to succeeding today. This book provides key insights into preparing better for a more data-driven future. A fascinating read for anyone looking to stay on top of how data science is revolutionizing just about everything. Jordan Morrow has done an amazing job taking a complex topic and synthesizing it for all to understand. Highly recommended." * Manuj Aggarwal, Founder and Chief Innovation Officer, TetraNoodle *"Jordan Morrow delivers a great follow-up to his first book, Be Data Literate. The phrase 'data driven' has evolved into a meaningless term and hollow buzzword through misuse and misunderstanding. With his new book, Jordan helps us understand what it actually means and why it matters. He then offers a simple, practical approach to help companies get there. For organizations and leaders who know there is value in their data but have struggled to unleash it, this is the book for you." * Brian Ferris, Chief Data, Analytics and Technology Officer, Loyalty NZ *"One of the pioneers in the field of data." * Jimmy Rex, investor, author and podcast host of The Jimmy Rex Show *"Jordan Morrow is a true authority on data literacy and the opportunity for organizations that want to become data driven. In this book, he covers all the critical ingredients organizations need to become truly data driven in a world that's been transformed by the Covid-19 pandemic. His second book is a great guide for leaders and practitioners alike and provides the necessary tools for transforming your business into a data-driven powerhouse." * Eva Murray, Lead Evangelist EMEA, Snowflake *"Jordan Morrow has followed his brilliant first book, Be Data Literate, with this masterpiece. It's a comprehensive and insightful book in which he shares his passion and experience in the data space to give everyone the power to harness the true power of data." * Bernard Marr, best-selling author, futurist, business and technology adviser *"This book aims high, with strong data culture principles and data literacy foundations, while maintaining significant focus on the strategy that guides data initiatives to successful completion and mission success. Failure is not an option in this data-intensive world. Be Data Driven is an excellent launchpad and mission guidebook for your organization's data-driven journey." * Kirk Borne, Chief Science Officer, DataPrime *"Jordan Morrow writes brilliantly, engages with the reader and, most crucially, demystifies the world of data and analytics. It all makes sense, even for those not familiar with the subject or struggling to understand. This book is a terrific start and for those passionate about business and success, essential!" * Mike Roe, CEO, Tensense.ai *Table of Contents Section - ONE: Foundational; Chapter - 01: A data-driven world; Chapter - 02: The impact of Covid-19 on organizations and data; Chapter - 03: Technologies advancing data and analytics, and the need for the human element; Chapter - 04: What is a data-driven organization?; Section - TWO: Gaps; Chapter - 05: Foundational skills gaps; Chapter - 06: Pillars of an organizational data strategy; Chapter - 07: The gap in leadership; Chapter - 08: The biggest hurdle: culture; Section - THREE: Building your data-driven organization; Chapter - 09: Decide your outcome; Chapter - 10: Build your strategy; Chapter - 11: Be data driven—start your journey!; Chapter - 12: References

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Book SynopsisToby Culshaw is the Talent Intelligence Leader at Worldwide Amazon Stores, leading a diverse global team of economists, consultants, business analysts and researchers in talent intelligence. Previously, he was Global Head of Talent Intelligence and Executive Recruitment Research at Royal Philips, the Dutch health technology group. He was named by Recruiter Magazine as one of the 11 Most Influential In-house Recruiters in 2017 and has consistently ranked every year from 2019 until 2023 and is an international speaker on sourcing, executive research and talent intelligence. Based in Brighton, UK he is also the founder of the Talent Intelligence Collective, a Talent Intelligence Mentor at Udder and a co-host of the Talent Intelligence Collective Podcast.Trade Review"Toby Culshaw wrote an insightful book to help you execute your talent strategy. What I like most about Talent Intelligence is how actionable it is. Toby shares years of his learnings and experience, and he explains in detail how you can apply it yourself through practical steps." * Anita Lettink, Keynote speaker and adviser on the future of work, partner at Strategic Management Centre and founder of HRTechRadar *"This is the first comprehensive discussion on Talent Intelligence I have seen. This is a topic much discussed, but little understood. Toby has finally given us a clear definition and a practical way to implement this powerful process." * Kevin Wheeler, Founder, The Future of Talent Institute *"Wow, from the maestro of TI, Toby himself. I was honoured when asked to read the book and comment and it is jam-packed with practical advice and real examples of talent intelligence in all its forms. A must read for business leaders and HR leaders alike who want to drive smarter business decisions. To quote from the book "the shifting mindset of operational to strategic is critical". Loved all of it - I will be buying the book for every member of our team for sure." * Alison Ettridge, Founder, Stratigens *"It's all about the data and the insights we can draw from it. I've felt this for a long time and this book and the work Toby has done confirms to me that this is a game changer! In an ever changing and highly competitive world the notion and discipline of talent intelligence is, for me, an essential part of an integrated talent strategy not only to compete but to win." * Denise Haylor, Former CHRO Royal Philips, Flextronics, Managing Director & Partner Boston Consulting Group *"Toby is a recognized & trusted expert in talent intelligence. Over the years he's proven to be one of the key leaders in this developing field. It's exciting to see how TI is developing and becoming more recognized as a valuable source of meaningful and actionable insights business leaders can leverage. In this text he brings together these experiences and a wide range of sources, it's a thorough essay on TI space and key reading for anyone interested in developing this knowledge." * Giles Harden, SVP People at INFARM *"Toby Culshaw and his insight on the function of Talent Intelligence as described in this text takes on and excels at creating a lexicon and foundational set of practices in the young and ever-growing space of Talent Intelligence. Creating a process is plenty hard, as is scoping a business case for change - both of which are in this text - yet defining a language for others to use in years to come is even harder. I am looking forward to applying many of these principles and labels to the products and services I use for the public and private sector companies we serve. Other leaders in recruiting, workforce planning, and analytics should review this lexicon and render into their own work so we can advance this ecosystem together as colleagues." * Andrew Gadonmski, Managing Director, Aspen Analytics *"The most inclusive and comprehensive work on Talent Intelligence I've seen to date. Toby's book captures the art and science of this continually evolving craft and emerging technology platforms complete with concrete and impactful examples. A must read for all leaders who see their competitive advantage coming from deeply understanding and acting on distilled insights from the internal and external talent landscape." * Cortney Erin, Vice President, Global Talent Acquisition Microsoft *"Timely and comprehensive examination of an often under-explored but critical area of talent strategy. Toby manages to come up with with something for everyone - from early to late adopters - as well as write a bit of a love letter to the subject." * Teresa Wykes, Global Head of Talent Intelligence, SAP *Table of Contents Chapter - 00: Introduction; Chapter - 01: Context; Chapter - 02: Types of Intelligence; Chapter - 03: The great debate; Chapter - 04: Building the case for Talent Intelligence; Chapter - 05: What type of work can TI functions support?; Chapter - 06: Metrics for Success and KPIs; Chapter - 07: Where to sit TI function within organizations; Chapter - 08: Talent Intelligence Maturity Model; Chapter - 09: Tooling and Resources; Chapter - 10: Potential structures of Talent Intelligence teams; Chapter - 11: Roles and skills needed in teams; Chapter - 12: Career pathing; Chapter - 13: In House and partner landscape; Chapter - 14: Examples of use of talent intelligence; Chapter - 15: What does good look like?; Chapter - 16: What is the future of Talent Intelligence?; Chapter - 17: Tales from the trenches; Chapter - 18: Well that’s a wrap

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Book SynopsisToby Culshaw is the Talent Intelligence Leader at Worldwide Amazon Stores, leading a diverse global team of economists, consultants, business analysts and researchers in talent intelligence. Previously, he was Global Head of Talent Intelligence and Executive Recruitment Research at Royal Philips, the Dutch health technology group. He was named by Recruiter Magazine as one of the 11 Most Influential In-house Recruiters in 2017 and has consistently ranked every year from 2019 until 2023 and is an international speaker on sourcing, executive research and talent intelligence. Based in Brighton, UK he is also the founder of the Talent Intelligence Collective, a Talent Intelligence Mentor at Udder and a co-host of the Talent Intelligence Collective Podcast.Trade Review"Toby Culshaw wrote an insightful book to help you execute your talent strategy. What I like most about Talent Intelligence is how actionable it is. Toby shares years of his learnings and experience, and he explains in detail how you can apply it yourself through practical steps." * Anita Lettink, Keynote speaker and adviser on the future of work, partner at Strategic Management Centre and founder of HRTechRadar *"This is the first comprehensive discussion on Talent Intelligence I have seen. This is a topic much discussed, but little understood. Toby has finally given us a clear definition and a practical way to implement this powerful process." * Kevin Wheeler, Founder, The Future of Talent Institute *"Wow, from the maestro of TI, Toby himself. I was honoured when asked to read the book and comment and it is jam-packed with practical advice and real examples of talent intelligence in all its forms. A must read for business leaders and HR leaders alike who want to drive smarter business decisions. To quote from the book "the shifting mindset of operational to strategic is critical". Loved all of it - I will be buying the book for every member of our team for sure." * Alison Ettridge, Founder, Stratigens *"It's all about the data and the insights we can draw from it. I've felt this for a long time and this book and the work Toby has done confirms to me that this is a game changer! In an ever changing and highly competitive world the notion and discipline of talent intelligence is, for me, an essential part of an integrated talent strategy not only to compete but to win." * Denise Haylor, Former CHRO Royal Philips, Flextronics, Managing Director & Partner Boston Consulting Group *"Toby is a recognized & trusted expert in talent intelligence. Over the years he's proven to be one of the key leaders in this developing field. It's exciting to see how TI is developing and becoming more recognized as a valuable source of meaningful and actionable insights business leaders can leverage. In this text he brings together these experiences and a wide range of sources, it's a thorough essay on TI space and key reading for anyone interested in developing this knowledge." * Giles Harden, SVP People at INFARM *"Toby Culshaw and his insight on the function of Talent Intelligence as described in this text takes on and excels at creating a lexicon and foundational set of practices in the young and ever-growing space of Talent Intelligence. Creating a process is plenty hard, as is scoping a business case for change - both of which are in this text - yet defining a language for others to use in years to come is even harder. I am looking forward to applying many of these principles and labels to the products and services I use for the public and private sector companies we serve. Other leaders in recruiting, workforce planning, and analytics should review this lexicon and render into their own work so we can advance this ecosystem together as colleagues." * Andrew Gadonmski, Managing Director, Aspen Analytics *"The most inclusive and comprehensive work on Talent Intelligence I've seen to date. Toby's book captures the art and science of this continually evolving craft and emerging technology platforms complete with concrete and impactful examples. A must read for all leaders who see their competitive advantage coming from deeply understanding and acting on distilled insights from the internal and external talent landscape." * Cortney Erin, Vice President, Global Talent Acquisition Microsoft *"Timely and comprehensive examination of an often under-explored but critical area of talent strategy. Toby manages to come up with with something for everyone - from early to late adopters - as well as write a bit of a love letter to the subject." * Teresa Wykes, Global Head of Talent Intelligence, SAP *Table of Contents Chapter - 00: Introduction; Chapter - 01: Context; Chapter - 02: Types of Intelligence; Chapter - 03: The great debate; Chapter - 04: Building the case for Talent Intelligence; Chapter - 05: What type of work can TI functions support?; Chapter - 06: Metrics for Success and KPIs; Chapter - 07: Where to sit TI function within organizations; Chapter - 08: Talent Intelligence Maturity Model; Chapter - 09: Tooling and Resources; Chapter - 10: Potential structures of Talent Intelligence teams; Chapter - 11: Roles and skills needed in teams; Chapter - 12: Career pathing; Chapter - 13: In House and partner landscape; Chapter - 14: Examples of use of talent intelligence; Chapter - 15: What does good look like?; Chapter - 16: What is the future of Talent Intelligence?; Chapter - 17: Tales from the trenches; Chapter - 18: Well that’s a wrap

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Book SynopsisMike Grigsby, based in Orlando, Florida, has more than 30 years' experience in the field of marketing analytics. He was formerly vice president of customer insights and advanced analytics at Brierley and Partners and of strategic business analysis and advanced analytics at Targetbase and has also held leadership positions at Hewlett-Packard and Gap. Previously an adjunct professor at the University of Texas at Dallas, he taught analytics at both graduate and undergraduate levels. He is the author of Advanced Customer Analytics, also published by Kogan Page.Trade Review"In Marketing Analytics, Mike Grigsby takes passionate marketing strategists on a practical, real-life journey for solving common marketing challenges. By combining the concepts and knowledge areas of statistics, marketing strategy and consumer behaviour, Grigsby recommends scientific and innovative solutions to common marketing problems in the current business environment. I highly recommend reading this book as it adds a completely new dimension to marketing science." * Kristina Domazetoska, Project Manager and Implementation Consultant at Insala – Talent Development and Mentoring Solutions *"Grigsby's book is the right blend of theory applied to the real-world large-scale data problems of marketing. It's exactly the book I wish I'd had when I started out in this field." * Jeff Weiner, Senior Director, Analytics, One10 *Table of Contents Section - 00: Introduction; Section - PART ONE: How can marketing analytics help you?; Chapter - 01: Overview of statistics; Chapter - 02: Consumer behaviour and marketing strategy; Chapter - 03: What is an insight?; Section - PART TWO: Dependent variable techniques; Chapter - 04: Modelling demand and elasticity; Chapter - 05: Polynomial distributed lags; Chapter - 06: Using Poisson regression; Chapter - 07: Logistic regression and market basket analysis; Chapter - 08: Survival modelling and lifetime value; Chapter - 09: Panel regression and same store sales; Chapter - 10: Introduction to forecasting; Section - PART THREE: Interrelationship techniques; Chapter - 11: Simultaneous equations; Chapter - 12: Principal components and factor analysis; Chapter - 13: Segmentation overview; Chapter - 14: Tools of segmentation; Section - PART FOUR: Focus on media and loyalty; Chapter - 15: Modelling marcom value; Chapter - 16: Media mix modelling; Chapter - 17: Overview of loyalty; Chapter - 18: Loyalty with SEM; Chapter - 19: The customer loyalty journey; Section - PART FIVE: More important topics for everyday marketing; Chapter - 20: Statistical testing; Chapter - 21: Introduction to Big Data; Chapter - 22: Conclusion - The finale; Chapter - 23: References; Chapter - 24: Further reading;

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Book SynopsisEdosa Odaro is an AI and data transformation leader who has helped countless international organizations deliver significant impact through data analytics, transformation strategy and intelligent interventions. He is Chief Data and Analytics Officer at Tawuniya and is on the board for the UK's National Institute for Health Data Science (HDR UK). Odaro has been named a Financial Times Top 100 Most Influential Leader and one of the UK's 30 Most Influential Black Leaders in FinTech.Trade Review"A masterclass in how to unlock the true value of data for your organization. Value-Driven Data is a must read for all data leaders." * Hartnell Ndungi, Chief Data Officer, Absa Group *"Value-Driven Data is a timely and practical guide to support us all with the challenge of unlocking and measuring the value of data. This thought provoking book is filled with practical examples to support frameworks and theories. A must read for all executives." * Dr Johanna Hutchinson, Chief Data Officer, BAE Systems and Board Member, The Royal Statistics Society *"A powerful reminder that data is not just a valuable asset, but a critical driver of business success and unlocking new value pools sitting at the intersection of technology and sustainable business." * Lamé Verre, Head of Strategy, Innovation & Sustainability, SSE Energy Customer Solutions and Global Future Council Member, World Economic Forum *"Value-Driven Data is an excellent book and a valuable resource for anyone looking to cut through the noise. It provides clarity on how to quantify the financial impact of data initiatives and effectively communicates with senior and non-technical audiences using clear and concise language." * Amy Shi-Nash, Chief Analytics & Data Officer, Tabcorp and Data Board Member, MIT Sloan School of Management *"Edosa has masterfully stitched together a collection of great examples with a set of tangible principles to guide readers on how to enhance their potential with data. The insights that this book provides are unique, the advice practical and the success stories applicable across industry sectors." * Mona Soni, Chief Technology Officer, formerly at S&P Global and Dow Jones *"Value-Driven Data offers a combination of deep knowledge and practical value for leaders guiding organizations through the responsible use of data. Odaro brings together a variety of perspectives from data practitioners and consultants to executive leadership in global businesses. I hope his shared knowledge will reach data professionals around the world and contribute to their success." * Simone Steel, Chief Data and Analytics Officer & CIO for Enterprise Data Platforms, Nationwide Building Society *"Value Driven Data cuts through the rumours and hearsay with real-life, no-nonsense examples of creating a data vision and value in practice. This is a comprehensive guide for both data professionals and business leaders. Once you have read it you won't want to do research without it." * Graeme McDermott, Chief Data Officer, Tempcover *"Provides insightful frameworks and considerations for every organization that wants to get more value out of data and analytics." * Gero Martin Gunkel, Data Science Leader & Chief Operating Officer (ZCAM), Zurich Insurance *"Value-Driven Data provides a comprehensive framework for developing a data vision that aligns with the overall strategy of an organisation. One of the most impressive aspects of the book is how it breaks down complex concepts into easy-to-understand language, making it an enjoyable read for anyone interested in data strategy, regardless of their level of expertise." * Rowland Agidee, Head of Data Management, UK Intellectual Property Office *"Edosa brings his experience and expertise together to remind us all of how expressing data value is fundamental to data driven transformation." * JC Lionti, Managing Director & Chief Data Officer, formerly at BNP Paribas Americas *"Edosa has done terrific work in producing this masterpiece! I like the way he has used data visions as the starting point and has linked all chapters to it by creating a practical and actionable book to help organizations realize their full potential." * Ram Kumar, Chief Data & Analytics Officer, Cigna *"Finally, a book that makes delivering value through data the number one priority. Business Leaders, whilst interested, do not really care how we as data professionals do it. Influencing top line, cost avoidance and bottom line are central to 99.9% of business strategies and so should also be the main focus when creating data strategies. Using real-world and highly relatable examples, Edosa has delivered an essential read for both data and business professionals." * Sam Richmond, Group Head of Data, The Go-Ahead Group *"Value-Driven Data is an incredible resource, full of frameworks and tools to help navigate the elusive topic of data value in an easy to digest format, with stories drawn from Edosa's long professional career. A valuable instrument in an era of cost optimisation, providing knowledge to the reader to aid in directing and articulating vision, value and creating pathways to overcome obstacles." * Stylianos Taxidis, Head of Data Science & AI, Costain Group *Table of Contents Chapter - 00: Introduction Section - ONE: Vision: Discovering and capturing data value opportunities Chapter - 01: What is data vision? Chapter - 02: Capturing data visions Chapter - 03: Why data visions of all size matter Chapter - 04: The destructive impact of data vision misalignment Chapter - 05: Simplifying data vision misalignments Section - TWO: Obstacle: The things that stand between data visions and data value realisation Chapter - 06: Obstacles of the past Chapter - 07: Obstacles of the future Chapter - 08: Obstacles of the present Section - THREE: Value: Identifying, capturing and communicating data value Chapter - 09: Capturing data value propositions Chapter - 10: Measuring data value for business case and operational assurance Chapter - 11: The data value measurement lifecycle Chapter - 12: A data value account for data profits and losses Chapter - 13: Presenting data value to the CXO, EXCO and the board Chapter - 14: Conclusion: Bringing it all together

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Book SynopsisEdosa Odaro is an AI and data transformation leader who has helped countless international organizations deliver significant impact through data analytics, transformation strategy and intelligent interventions. He is Chief Data and Analytics Officer at Tawuniya and is on the board for the UK's National Institute for Health Data Science (HDR UK). Odaro has been named a Financial Times Top 100 Most Influential Leader and one of the UK's 30 Most Influential Black Leaders in FinTech.Trade Review"A masterclass in how to unlock the true value of data for your organization. Value-Driven Data is a must read for all data leaders." * Hartnell Ndungi, Chief Data Officer, Absa Group *"Value-Driven Data is a timely and practical guide to support us all with the challenge of unlocking and measuring the value of data. This thought provoking book is filled with practical examples to support frameworks and theories. A must read for all executives." * Dr Johanna Hutchinson, Chief Data Officer, BAE Systems and Board Member, The Royal Statistics Society *"A powerful reminder that data is not just a valuable asset, but a critical driver of business success and unlocking new value pools sitting at the intersection of technology and sustainable business." * Lamé Verre, Head of Strategy, Innovation & Sustainability, SSE Energy Customer Solutions and Global Future Council Member, World Economic Forum *"Value-Driven Data is an excellent book and a valuable resource for anyone looking to cut through the noise. It provides clarity on how to quantify the financial impact of data initiatives and effectively communicates with senior and non-technical audiences using clear and concise language." * Amy Shi-Nash, Chief Analytics & Data Officer, Tabcorp and Data Board Member, MIT Sloan School of Management *"Edosa has masterfully stitched together a collection of great examples with a set of tangible principles to guide readers on how to enhance their potential with data. The insights that this book provides are unique, the advice practical and the success stories applicable across industry sectors." * Mona Soni, Chief Technology Officer, formerly at S&P Global and Dow Jones *"Value-Driven Data offers a combination of deep knowledge and practical value for leaders guiding organizations through the responsible use of data. Odaro brings together a variety of perspectives from data practitioners and consultants to executive leadership in global businesses. I hope his shared knowledge will reach data professionals around the world and contribute to their success." * Simone Steel, Chief Data and Analytics Officer & CIO for Enterprise Data Platforms, Nationwide Building Society *"Value Driven Data cuts through the rumours and hearsay with real-life, no-nonsense examples of creating a data vision and value in practice. This is a comprehensive guide for both data professionals and business leaders. Once you have read it you won't want to do research without it." * Graeme McDermott, Chief Data Officer, Tempcover *"Provides insightful frameworks and considerations for every organization that wants to get more value out of data and analytics." * Gero Martin Gunkel, Data Science Leader & Chief Operating Officer (ZCAM), Zurich Insurance *"Value-Driven Data provides a comprehensive framework for developing a data vision that aligns with the overall strategy of an organisation. One of the most impressive aspects of the book is how it breaks down complex concepts into easy-to-understand language, making it an enjoyable read for anyone interested in data strategy, regardless of their level of expertise." * Rowland Agidee, Head of Data Management, UK Intellectual Property Office *"Edosa brings his experience and expertise together to remind us all of how expressing data value is fundamental to data driven transformation." * JC Lionti, Managing Director & Chief Data Officer, formerly at BNP Paribas Americas *"Edosa has done terrific work in producing this masterpiece! I like the way he has used data visions as the starting point and has linked all chapters to it by creating a practical and actionable book to help organizations realize their full potential." * Ram Kumar, Chief Data & Analytics Officer, Cigna *"Finally, a book that makes delivering value through data the number one priority. Business Leaders, whilst interested, do not really care how we as data professionals do it. Influencing top line, cost avoidance and bottom line are central to 99.9% of business strategies and so should also be the main focus when creating data strategies. Using real-world and highly relatable examples, Edosa has delivered an essential read for both data and business professionals." * Sam Richmond, Group Head of Data, The Go-Ahead Group *"Value-Driven Data is an incredible resource, full of frameworks and tools to help navigate the elusive topic of data value in an easy to digest format, with stories drawn from Edosa's long professional career. A valuable instrument in an era of cost optimisation, providing knowledge to the reader to aid in directing and articulating vision, value and creating pathways to overcome obstacles." * Stylianos Taxidis, Head of Data Science & AI, Costain Group *Table of Contents Chapter - 00: Introduction Section - ONE: Vision: Discovering and capturing data value opportunities Chapter - 01: What is data vision? Chapter - 02: Capturing data visions Chapter - 03: Why data visions of all size matter Chapter - 04: The destructive impact of data vision misalignment Chapter - 05: Simplifying data vision misalignments Section - TWO: Obstacle: The things that stand between data visions and data value realisation Chapter - 06: Obstacles of the past Chapter - 07: Obstacles of the future Chapter - 08: Obstacles of the present Section - THREE: Value: Identifying, capturing and communicating data value Chapter - 09: Capturing data value propositions Chapter - 10: Measuring data value for business case and operational assurance Chapter - 11: The data value measurement lifecycle Chapter - 12: A data value account for data profits and losses Chapter - 13: Presenting data value to the CXO, EXCO and the board Chapter - 14: Conclusion: Bringing it all together

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Book SynopsisNeetan Chopra is a C-suite level senior digital leader with a track record of driving change and innovation at established enterprises. In his three-decade career, he has led digital transformation in global enterprises operating diverse business models across the aviation, travel, logistics, retail, food and beverage, real estate and entertainment industry sectors. He is currently Chief Digital and Information Officer at IndiGo (InterGlobe Aviation Ltd) in Gurugram, India; prior to this, he also held roles at Dubai Holding, Emirates Airlines and Accenture. He sits on the boards of multiple tech start-ups, has built multiple global innovation labs including at Oxford University and Carnegie Mellon University and is an Adjunct Professor at Botho University, Botswana. He is recognized by the Constellation Research Business Transformation 150 as one of the world's top global executives leading innovative business transformation efforts in their organizations.Trade Review"An insightful, practitioners' guide full of pragmatic ideas and valuable learnings from decades of experience. A must-read for executives vying for industry leadership in digital." * Joydeep Sengupta, Senior Partner, McKinsey & Company *"More than 80% of digital transformation projects fail inside large organizations not through lack of trying. Every organization looking to crack the code for success must read Neetan Chopra's book. By taking a practitioner's point of view, he draws from three decades of experience to provide a proven methodology known as the Honeycomb Framework. Accelerated Digital Transformation is a must-read book for digital leaders." * R ‘Ray’ Wang, Founder and Chairman, Constellation Research *"We live in a time where the fog of technology is often overwhelming, difficult to dissect and changing so rapidly it becomes difficult to have confidence in our decision making. Neetan Chopra takes the mystery out of creating successful digital transformations for companies and their clients in a way that brings light and clarity to an otherwise challenging process. The insights he has gathered through his years of technology experience provide the keys for those who are looking to unlock value during these extraordinary times." * Tim Kobe, Founder and CEO, Eight Inc. *"Every enterprise must succeed on a digital journey to remain relevant, serve customers and add value. Accelerated Digital Transformation provides you with a pragmatic guide and framework to achieve progress and success. I appreciate Neetan Chopra's storytelling approach and many lessons of everyday role models delivering extraordinary customer service. These stories demonstrate the Uplifting Service ethos that earns customer praise and social media attention." * Ron Kaufman, New York Times Bestselling Author, Uplifting Service: The Proven Path to Delighting Your Customers, Colleagues, and Everyone Else You Meet *"Only if one has lived through or, even better, driven digital transformation of a major company, can one seriously understand what it means to write a book about it that is worth reading. Neetan Chopra is exactly one of these few leaders who has lived through such digital transformations and knows exactly what it means, what works and what doesn't. Chopra's book is probably one of the very few books about digital transformation really worth reading, as it is not yet another consultant textbook, far remote from reality, but written by true experience and painful learnings." * Patrick Naef, Managing Partner, Boyden *"Accelerated Digital Transformation deftly fuses practical examples and actionable insights from Neetan Chopra's vast digital experience, with deep foundational learning, borne out of his global academic pursuits. Chopra's storytelling approach, coupled with innovative interventions, such as co-authoring a chapter with an AI-bot, make the book both engaging and first-of-a-kind read. We highly recommend this book, for anyone looking to navigate the ever-evolving digital landscape and staying ahead of the game in the digital era." * Prof Dr Reinhard Jung, Dean, School of Management, University of St Gallen & Prof Dr Ulrike Baumöl, Executive Director, Executive MBA HSG in Business Engineering, University of St Gallen *"Having seen firsthand how Neetan Chopra executes successful digital transformation where others have struggled, I am grateful he has taken the time to write down his framework. His deliberate 'cell by cell' strategy is what it takes to assess, learn and succeed in this complicated mix of technical, business and cultural transformation. And a bonus, he demonstrates learning with this framework by co-authoring one chapter with an AI bot... brilliant!" * Jana Eggers, CEO, Nara Logics *"All transformations, digital or otherwise, are in essence a human journey of change. I like Chopra's storytelling, a colloquial approach to the intimidating topic of digital transformation for business leaders. This will connect with people across all walks of life, demystifying what it takes to thrive in the digital era and create exponential outcomes. The six global experts, the honeycomb archetypes, provide an additional human touch, sharing their experiences and wisdom, using Chopra's Accelerated Digital Transformation as a platform. A must read." * Raj Jain, Former CEO, Bennett Coleman & Co Limited (Times Group) *"Organizations need simple frameworks by which they can plan their digital transitions. Neetan Chopra's efforts on achieving this through a well thought out 'Honeycomb Framework' is commendable. His building blocks of digital transformation provide a succinct and clear framework through which readers can apply these in the context of their organizations. The future is about organizations which will survive and thrive in a digitally driven business ecosystem. Chopra's book will help organizations survive and thrive in a VUCA world." * Krishnakumar Natarajan, Co-founder & Former Executive Chairperson, LTIMindtree *"Chopra's new book helps you reduce bad friction into a manageable hexagon comb while introducing good friction to sweeten the honey from digital transformation." * Soon Yu, Author, Friction: Adding Value by Making People Work For It *Table of Contents Chapter - 01: Breaking organizational inertia; Chapter - 02: Working the Honeycomb – disrupt phase; Chapter - 03: Working the Honeycomb – digital capabilities; Chapter - 04: Accelerated possibilities; Chapter - 05: Honeycomb as a platform; Chapter - 06: The Honeycomb hacks; Chapter - 07: Reflections;

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Book SynopsisNeetan Chopra is a C-suite level senior digital leader with a track record of driving change and innovation at established enterprises. In his three-decade career, he has led digital transformation in global enterprises operating diverse business models across the aviation, travel, logistics, retail, food and beverage, real estate and entertainment industry sectors. He is currently Chief Digital and Information Officer at IndiGo (InterGlobe Aviation Ltd) in Gurugram, India; prior to this, he also held roles at Dubai Holding, Emirates Airlines and Accenture. He sits on the boards of multiple tech start-ups, has built multiple global innovation labs including at Oxford University and Carnegie Mellon University and is an Adjunct Professor at Botho University, Botswana. He is recognized by the Constellation Research Business Transformation 150 as one of the world's top global executives leading innovative business transformation efforts in their organizations.Trade Review"An insightful, practitioners' guide full of pragmatic ideas and valuable learnings from decades of experience. A must-read for executives vying for industry leadership in digital." * Joydeep Sengupta, Senior Partner, McKinsey & Company *"More than 80% of digital transformation projects fail inside large organizations not through lack of trying. Every organization looking to crack the code for success must read Neetan Chopra's book. By taking a practitioner's point of view, he draws from three decades of experience to provide a proven methodology known as the Honeycomb Framework. Accelerated Digital Transformation is a must-read book for digital leaders." * R ‘Ray’ Wang, Founder and Chairman, Constellation Research *"We live in a time where the fog of technology is often overwhelming, difficult to dissect and changing so rapidly it becomes difficult to have confidence in our decision making. Neetan Chopra takes the mystery out of creating successful digital transformations for companies and their clients in a way that brings light and clarity to an otherwise challenging process. The insights he has gathered through his years of technology experience provide the keys for those who are looking to unlock value during these extraordinary times." * Tim Kobe, Founder and CEO, Eight Inc. *"Every enterprise must succeed on a digital journey to remain relevant, serve customers and add value. Accelerated Digital Transformation provides you with a pragmatic guide and framework to achieve progress and success. I appreciate Neetan Chopra's storytelling approach and many lessons of everyday role models delivering extraordinary customer service. These stories demonstrate the Uplifting Service ethos that earns customer praise and social media attention." * Ron Kaufman, New York Times Bestselling Author, Uplifting Service: The Proven Path to Delighting Your Customers, Colleagues, and Everyone Else You Meet *"Only if one has lived through or, even better, driven digital transformation of a major company, can one seriously understand what it means to write a book about it that is worth reading. Neetan Chopra is exactly one of these few leaders who has lived through such digital transformations and knows exactly what it means, what works and what doesn't. Chopra's book is probably one of the very few books about digital transformation really worth reading, as it is not yet another consultant textbook, far remote from reality, but written by true experience and painful learnings." * Patrick Naef, Managing Partner, Boyden *"Accelerated Digital Transformation deftly fuses practical examples and actionable insights from Neetan Chopra's vast digital experience, with deep foundational learning, borne out of his global academic pursuits. Chopra's storytelling approach, coupled with innovative interventions, such as co-authoring a chapter with an AI-bot, make the book both engaging and first-of-a-kind read. We highly recommend this book, for anyone looking to navigate the ever-evolving digital landscape and staying ahead of the game in the digital era." * Prof Dr Reinhard Jung, Dean, School of Management, University of St Gallen & Prof Dr Ulrike Baumöl, Executive Director, Executive MBA HSG in Business Engineering, University of St Gallen *"Having seen firsthand how Neetan Chopra executes successful digital transformation where others have struggled, I am grateful he has taken the time to write down his framework. His deliberate 'cell by cell' strategy is what it takes to assess, learn and succeed in this complicated mix of technical, business and cultural transformation. And a bonus, he demonstrates learning with this framework by co-authoring one chapter with an AI bot... brilliant!" * Jana Eggers, CEO, Nara Logics *"All transformations, digital or otherwise, are in essence a human journey of change. I like Chopra's storytelling, a colloquial approach to the intimidating topic of digital transformation for business leaders. This will connect with people across all walks of life, demystifying what it takes to thrive in the digital era and create exponential outcomes. The six global experts, the honeycomb archetypes, provide an additional human touch, sharing their experiences and wisdom, using Chopra's Accelerated Digital Transformation as a platform. A must read." * Raj Jain, Former CEO, Bennett Coleman & Co Limited (Times Group) *"Organizations need simple frameworks by which they can plan their digital transitions. Neetan Chopra's efforts on achieving this through a well thought out 'Honeycomb Framework' is commendable. His building blocks of digital transformation provide a succinct and clear framework through which readers can apply these in the context of their organizations. The future is about organizations which will survive and thrive in a digitally driven business ecosystem. Chopra's book will help organizations survive and thrive in a VUCA world." * Krishnakumar Natarajan, Co-founder & Former Executive Chairperson, LTIMindtree *"Chopra's new book helps you reduce bad friction into a manageable hexagon comb while introducing good friction to sweeten the honey from digital transformation." * Soon Yu, Author, Friction: Adding Value by Making People Work For It *Table of Contents Chapter - 01: Breaking organizational inertia; Chapter - 02: Working the Honeycomb – disrupt phase; Chapter - 03: Working the Honeycomb – digital capabilities; Chapter - 04: Accelerated possibilities; Chapter - 05: Honeycomb as a platform; Chapter - 06: The Honeycomb hacks; Chapter - 07: Reflections;

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Book SynopsisJordan Morrow is known as the "Godfather of Data Literacy", having helped pioneer the field by building one of the world's first data literacy programs. He is the founder and CEO of Bodhi Data, served as the Chair of the Advisory Board for The Data Literacy Project and has helped companies and organizations around the world, including the United Nations, build and understand data literacy. Morrow is the author of three books: Be Data Literate, Be Data Driven, and Be Data Analytical, all published by Kogan Page. He is based near Salt Lake City, Utah.Trade Review"A must-read for anyone looking to harness the power of data. Be Data Analytical stands out as a comprehensive guide that empowers readers to unlock the hidden potential within their data, driving innovation and growth in any field." * Bernard Marr, Founder & CEO, Bernard Marr & Co *"If you're looking for a practical guide to learn about the four levels of analytics, look no further than Be Data Analytical. Jordan Morrow's hands-on approach to teaching data analytics makes the book an invaluable resource for anyone who wants to learn the skills needed to succeed in the field. The clear explanations, practical examples and content breakdown make this book an excellent choice for both beginners and experienced professionals." * Chandra Donelson, Washington D.C. Chapter Lead, Women in Data *"Jordan's passion and enthusiasm for data shines through. Breaking down analytics into four accessible levels means this book is for everyone. Its real-life examples and analogies bring to life the importance of understanding and implementing good analytics." * Susan Walsh, Founder & Managing Director, The Classification Guru Ltd *"This book provides an excellent framework for data-driven decision-making in organizations. By framing the analytics implementations progressively through the four levels of analytics, Be Data Analytical is easy to follow as an analytics guidebook. At each stage, the book covers key definitions, roles of the different enterprise players, numerous business examples and strategy suggestions to get the analytics job done." * Kirk Borne, Founder, Data Leadership Group *"Data Analytics is a crucial aspect of decision-making in the modern business landscape, and this book provides a comprehensive guide to understanding its nuances. The author's expertise and passion for the subject is present in every chapter, making this book a must-read for anyone seeking to improve their data literacy and enhance their decision-making skills. I highly recommend this book to anyone looking to unlock the power of data analytics in their organization." * Esther Munyi, Chief Data and Analytics Officer, Sasfin *"Be Data Analytical is a book about leadership, decision making, staying ahead and having your own built-in systems. A consummate storyteller, Jordan speaks to those who know this space and those who perhaps need to. The data environment has changed forever and the complexity and challenge for leaders means the rule book we used to follow, and our previous frames of reference, are redundant. New ways of thinking and improving decision making are therefore vital." * Mike Roe, CEO, Tensense.ai *"Ingenious! Jordan's engaging work propels the reader from data literacy to data analysis." * Major General Dustin Shultz *Table of Contents Chapter - 00: Introduction; Section - ONE: Data and analytics; Chapter - 01: Defining data and analytics; Chapter - 02: Defining the four levels of analytics; Chapter - 03: The power of analytics in decision making; Section - TWO: The four levels of analytics - define, empower, understand and learn; Chapter - 04: Descriptive analytics; Chapter - 05: How are descriptive analytics used today?; Chapter - 06: How individuals and organizations can improve in descriptive analytics; Chapter - 07: Diagnostic analytics; Chapter - 08: How are diagnostic analytics used today?; Chapter - 09: How individuals and organizations can improve in diagnostic analytics; Chapter - 10: Predictive analytics; Chapter - 11: How are predictive analytics used today?; Chapter - 12: How individuals and organizations can improve in predictive analytics; Chapter - 13: Prescriptive analytics; Chapter - 14: How are prescriptive analytics used today?; Chapter - 15: How individuals and organizations can improve in prescriptive analytics; Section - Three: Bringing it all together; Chapter - 16: Using all four levels of analytics to empower decision making; Chapter - 17: Conclusion;

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Book SynopsisJordan Morrow is known as the "Godfather of Data Literacy", having helped pioneer the field by building one of the world's first data literacy programs. He is the founder and CEO of Bodhi Data, served as the Chair of the Advisory Board for The Data Literacy Project and has helped companies and organizations around the world, including the United Nations, build and understand data literacy. Morrow is the author of three books: Be Data Literate, Be Data Driven, and Be Data Analytical, all published by Kogan Page. He is based near Salt Lake City, Utah.Trade Review"A must-read for anyone looking to harness the power of data. Be Data Analytical stands out as a comprehensive guide that empowers readers to unlock the hidden potential within their data, driving innovation and growth in any field." * Bernard Marr, Founder & CEO, Bernard Marr & Co *"If you're looking for a practical guide to learn about the four levels of analytics, look no further than Be Data Analytical. Jordan Morrow's hands-on approach to teaching data analytics makes the book an invaluable resource for anyone who wants to learn the skills needed to succeed in the field. The clear explanations, practical examples and content breakdown make this book an excellent choice for both beginners and experienced professionals." * Chandra Donelson, Washington D.C. Chapter Lead, Women in Data *"Jordan's passion and enthusiasm for data shines through. Breaking down analytics into four accessible levels means this book is for everyone. Its real-life examples and analogies bring to life the importance of understanding and implementing good analytics." * Susan Walsh, Founder & Managing Director, The Classification Guru Ltd *"This book provides an excellent framework for data-driven decision-making in organizations. By framing the analytics implementations progressively through the four levels of analytics, Be Data Analytical is easy to follow as an analytics guidebook. At each stage, the book covers key definitions, roles of the different enterprise players, numerous business examples and strategy suggestions to get the analytics job done." * Kirk Borne, Founder, Data Leadership Group *"Data Analytics is a crucial aspect of decision-making in the modern business landscape, and this book provides a comprehensive guide to understanding its nuances. The author's expertise and passion for the subject is present in every chapter, making this book a must-read for anyone seeking to improve their data literacy and enhance their decision-making skills. I highly recommend this book to anyone looking to unlock the power of data analytics in their organization." * Esther Munyi, Chief Data and Analytics Officer, Sasfin *"Be Data Analytical is a book about leadership, decision making, staying ahead and having your own built-in systems. A consummate storyteller, Jordan speaks to those who know this space and those who perhaps need to. The data environment has changed forever and the complexity and challenge for leaders means the rule book we used to follow, and our previous frames of reference, are redundant. New ways of thinking and improving decision making are therefore vital." * Mike Roe, CEO, Tensense.ai *"Ingenious! Jordan's engaging work propels the reader from data literacy to data analysis." * Major General Dustin Shultz *Table of Contents Chapter - 00: Introduction; Section - ONE: Data and analytics; Chapter - 01: Defining data and analytics; Chapter - 02: Defining the four levels of analytics; Chapter - 03: The power of analytics in decision making; Section - TWO: The four levels of analytics - define, empower, understand and learn; Chapter - 04: Descriptive analytics; Chapter - 05: How are descriptive analytics used today?; Chapter - 06: How individuals and organizations can improve in descriptive analytics; Chapter - 07: Diagnostic analytics; Chapter - 08: How are diagnostic analytics used today?; Chapter - 09: How individuals and organizations can improve in diagnostic analytics; Chapter - 10: Predictive analytics; Chapter - 11: How are predictive analytics used today?; Chapter - 12: How individuals and organizations can improve in predictive analytics; Chapter - 13: Prescriptive analytics; Chapter - 14: How are prescriptive analytics used today?; Chapter - 15: How individuals and organizations can improve in prescriptive analytics; Section - Three: Bringing it all together; Chapter - 16: Using all four levels of analytics to empower decision making; Chapter - 17: Conclusion;

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Book SynopsisThomas C Redman is known as the 'Data Doc' and is the founder and President of Data Quality Solutions. Through this company he helps people and organizations think about data and data quality in new and exciting ways. Based in Rumson, New Jersey, he previously worked at AT&T where he formed their data quality lab.Trade Review"Based on my own decades-long experience working with organizations on removing data-related barriers and building data-driven strategies, I could not agree more with Tom's guidance to put people at the center. He's on to something massively important here - if you internalize and act on the people-focused principles he's suggesting, you will no doubt accelerate and amplify your impact on the business." * Ted Friedman, Former Gartner Analyst and Industry Thought-Leader *"For any organisation to succeed in the 21st Century, it needs people and data. Moreover, as Tom Redman explains in People and Data, when these two elements unite and when the benefits of data are extended to everyone in the organisation you can transform your business. Whether you are a leader, manager or worker or whether you work in HR, Finance, Operations or Marketing, I heartily recommend reading People and Data." * David Green, Co-author of Excellence in People Analytics, Managing Partner at Insight222, and host of the Digital HR Leaders podcast. *"People and Data offers great insights and advice on how organizations can unleash "real people" , working together, to solve the data quality problem, once and for all. We could all benefit from Tom's optimism and experience." * Maria Villar, Head of Enterprise Data Strategy & Transformation, SAP North America *"People and Data is the provocation that many data managers and executives need to spur them into action. Today's world is driven by data, but as Tom reminds us, if the data is poor (garbage in), then the outcomes are as well (garbage out). Tom's solution for maintaining quality data lies not in technology but in people - how they are organized, what tasks they are given, what culture they create, how they are motivated, promoted and trained. Tom explores all aspects of building a world-class data organization." * Theresa Kushner, former Head of Innovation Center, NTT Data, North America *"Tom Redman has a knack for taking the complex world of data and making it simple to understand and improve. What businesses have struggled with for decades is delivered in this next generational approach: data is predominantly a people issue and must be considered a team sport. In this new book, Redman brings solutions that highlight how regular people working together within and across organizations, under the direction of senior leaders, can finally solve this very expensive and seemingly endless enigma and no longer need to stand on the data sidelines." * Bob Palermo, former Vice President, Performance Excellence, Shell *"The book, People and Data: Uniting to transform your business is an exceptional resource by one of the world's leading thinkers and practitioners on 'data' - Dr. Thomas Redman. Every professional, with "data" in their title or not, should read Tom's book and learn from his experiences developed over 25+ years as the 'Data Doc'." * Anne Marie Smith, Ph.D., Alabama Yankee Systems, LLC *"Nothing of quality happens without quality people, fueled with quality data, making quality decisions. Here Redman establishes the case, roadmap and tools for dramatic business growth through quality data. Lead People, Manage Assets goes the adage. Tom shows us sensible ways to Lead regular people in uniting to successfully manage the unique assets of data, and information technology. Fortune Favors The Brave: so read People and Data - then lead bravely for sustained business growth." * Robert Pautke, Founder & Leadership Coach, SOAR with Purpose, LLC *Table of Contents Chapter - 00: Introduction; Section - ONE: The big picture; Chapter - 01: Ann’s data Tuesday; Chapter - 02: The opportunity and the problem; Chapter - 03: Building a better organization for data; Section - TWO: People; Chapter - 04: The data generation and provocateurs; Chapter - 05: All roads lead through quality; Chapter - 06: Putting data to work; Section - THREE: Data is a team sport; Chapter - 07: Fat organizational pipes; Chapter - 08: Don’t confuse apples and oranges; Chapter - 09: Dream big, but change the culture one project at a time; Section - 10: The data teams companies need now; Section - 11: Conclusion - Courage required; Section - 12: Resource Centre 1 - Toolkit; Section - 13: Resource Centre 2 - Curriculum for training regular people;

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Book SynopsisThomas C Redman is known as the 'Data Doc' and is the founder and President of Data Quality Solutions. Through this company he helps people and organizations think about data and data quality in new and exciting ways. Based in Rumson, New Jersey, he previously worked at AT&T where he formed their data quality lab.Trade Review"Based on my own decades-long experience working with organizations on removing data-related barriers and building data-driven strategies, I could not agree more with Tom's guidance to put people at the center. He's on to something massively important here - if you internalize and act on the people-focused principles he's suggesting, you will no doubt accelerate and amplify your impact on the business." * Ted Friedman, Former Gartner Analyst and Industry Thought-Leader *"For any organisation to succeed in the 21st Century, it needs people and data. Moreover, as Tom Redman explains in People and Data, when these two elements unite and when the benefits of data are extended to everyone in the organisation you can transform your business. Whether you are a leader, manager or worker or whether you work in HR, Finance, Operations or Marketing, I heartily recommend reading People and Data." * David Green, Co-author of Excellence in People Analytics, Managing Partner at Insight222, and host of the Digital HR Leaders podcast. *"People and Data offers great insights and advice on how organizations can unleash "real people" , working together, to solve the data quality problem, once and for all. We could all benefit from Tom's optimism and experience." * Maria Villar, Head of Enterprise Data Strategy & Transformation, SAP North America *"People and Data is the provocation that many data managers and executives need to spur them into action. Today's world is driven by data, but as Tom reminds us, if the data is poor (garbage in), then the outcomes are as well (garbage out). Tom's solution for maintaining quality data lies not in technology but in people - how they are organized, what tasks they are given, what culture they create, how they are motivated, promoted and trained. Tom explores all aspects of building a world-class data organization." * Theresa Kushner, former Head of Innovation Center, NTT Data, North America *"Tom Redman has a knack for taking the complex world of data and making it simple to understand and improve. What businesses have struggled with for decades is delivered in this next generational approach: data is predominantly a people issue and must be considered a team sport. In this new book, Redman brings solutions that highlight how regular people working together within and across organizations, under the direction of senior leaders, can finally solve this very expensive and seemingly endless enigma and no longer need to stand on the data sidelines." * Bob Palermo, former Vice President, Performance Excellence, Shell *"The book, People and Data: Uniting to transform your business is an exceptional resource by one of the world's leading thinkers and practitioners on 'data' - Dr. Thomas Redman. Every professional, with "data" in their title or not, should read Tom's book and learn from his experiences developed over 25+ years as the 'Data Doc'." * Anne Marie Smith, Ph.D., Alabama Yankee Systems, LLC *"Nothing of quality happens without quality people, fueled with quality data, making quality decisions. Here Redman establishes the case, roadmap and tools for dramatic business growth through quality data. Lead People, Manage Assets goes the adage. Tom shows us sensible ways to Lead regular people in uniting to successfully manage the unique assets of data, and information technology. Fortune Favors The Brave: so read People and Data - then lead bravely for sustained business growth." * Robert Pautke, Founder & Leadership Coach, SOAR with Purpose, LLC *Table of Contents Chapter - 00: Introduction; Section - ONE: The big picture; Chapter - 01: Ann’s data Tuesday; Chapter - 02: The opportunity and the problem; Chapter - 03: Building a better organization for data; Section - TWO: People; Chapter - 04: The data generation and provocateurs; Chapter - 05: All roads lead through quality; Chapter - 06: Putting data to work; Section - THREE: Data is a team sport; Chapter - 07: Fat organizational pipes; Chapter - 08: Don’t confuse apples and oranges; Chapter - 09: Dream big, but change the culture one project at a time; Section - 10: The data teams companies need now; Section - 11: Conclusion - Courage required; Section - 12: Resource Centre 1 - Toolkit; Section - 13: Resource Centre 2 - Curriculum for training regular people;

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Book SynopsisBernard Marr is one of the leading voices in Technology and Innovation. A futurist and strategic performance consultant, he has advised many of the world's best-known organizations on their business and data strategies. A frequent keynote speaker, he also writes on the topic of data and analytics for various publications including Forbes and the Huffington Post. Bernard Marr is also the author of Data Strategy (2021) and The Intelligence Revolution (2020) published by Kogan Page.Trade Review"Without a doubt human capability (talent + leadership + organization + HR) increasingly delivers value to all stakeholders. This excellent book provides business and HR leaders the information required to improve decision making. Bernard's insights on analytics and AI will be the keys for progress." * Dave Ulrich, Rensis Likert Professor, Ross School of Business, University of Michigan Partner, The RBL Group *"If anyone was going to publish a book about the impact of the latest technology developments such as AI on the field of HR and People Analytics my bets were on Bernard Marr. And you won't be disappointed. The book offers a deep dive into the world of data of every kind, every possible use case, honest overview of technology and important considerations. It has never been more critical to educate ourselves about it." * Maja Luckos, VP, Employee Success, Salesforce *"This book propelled me into a world of possibilities for HR leaders in embracing the 'intelligence revolution' to shape people strategies that add value to their organizations and their people. It's enlightened me to the power of AI-enabled HR and how I might use it, and it's made me want to learn more. This is a must read for all HR leaders." * Linda Sleath, Group HR Director, Topps Tiles Plc. *"Data-Driven HR strikes a nice balance between exploring emerging trends in people analytics while primarily serving as a practical guide to HR professionals at any stage of their data journey. The second edition seamlessly weaves AI into a narrative that's easy to engage with and is packed full of examples that bring the theories to life." * Mark Ferrie, People Analytics Director, Meta *"Data-Driven HR is a terrific overview of the enormous world of people analytics and AI. For people trying to understand this important space, this book shows you the way." * Josh Bersin, Global Industry Analyst and CEO of The Josh Bersin Company *"Data, analytics and AI provides to elevate HR from its traditional role as a support function to one of a strategic partner creating value for the enterprise, its customers and its employees. There's a well-thumbed copy of the first edition of Data Driven HR on my bookshelf, and in this timely update Marr, one of the most knowledgeable people on the topic, explains how data and AI can enable HR to drive better decision making about people, deliver an enhanced service to employees; and make HR processes more efficient." * David Green, Managing Partner at Insight222, co-author of Excellence in People Analytics, and host of the Digital HR Leaders podcast. *"Bernard Marr has once again delivered an indispensable guide to harnessing the power of data, analytics and AI in HR. This updated edition thoroughly captures the latest innovations shaping human resources while still being accessible for HR professionals at any level. Through compelling examples and clear frameworks, Marr demonstrates how to drive business value through evidence-based talent practices. This is a must-read playbook for any HR leader looking to build capabilities in data-driven decision-making." * Professor Max Blumberg, PhD, University of Leeds *"This is a great guide for HR professionals who are grappling with the transition to becoming data led. It's easy to read, and with real examples and case studies across the employee lifecycle, it's also a pragmatic resource to have in your HR toolkit." * Ashish Sinha Korn Ferry Head of People Analytics, AI & Strategy EMEA Practice Leader *"AI is transforming the world of work and our personal lives. With a people-centric approach, Bernard Marr demystifies data driven AI enabled HR with context, thought provoking insights and examples of AI at the time this book was written. We all have a role to play when it comes to this rapidly evolving space as the output of AI will be a reflection of our culture and values. Staying on top of leading practices, lessons learned, emerging regulations and standards is critical so we can unlock AI's potential and value add to the business, our customers and employees while minimizing risk. This book sets the foundation so we can do just that!" * Terilyn Juarez Monroe, Terilyn Juarez Monroe, Chief People Officer *"Data-Driven HR is an indispensable resource for Career Services professionals looking to equip their students with cutting-edge strategies in today's competitive job market. This comprehensive book offers invaluable insights into recruitment and candidate selection, employer branding, pinpointing the most effective recruitment channels, and harnessing AI-enhanced automation to identify and assess the best candidates for businesses. It's a game-changer for career advisors committed to empowering their students with the knowledge and skills needed to excel in the evolving world of talent acquisition and HR." * Dr. Amber Wigmore Álvarez, Associate Professor, IE Business School and IE University *Table of Contents Chapter - 00: Preface; Section - ONE: Data, Analytics and AI in HR; Chapter - 01: How data and AI are transforming HR; Chapter - 02: How data and AI have come to revolutionise HR; Chapter - 03: The Data, Analytics and AI tools available to HR; Section - TWO: Data-Driven and AI-enabled HR in Practice; Chapter - 04: Better HR insights and decision-making; Chapter - 05: Recruitment and candidate selection; Chapter - 06: Employee Onboarding; Chapter - 07: Performance Monitoring and Management; Chapter - 08: Employee Training and Development; Chapter - 09: Performance monitoring and management; Chapter - 10: Identify the use cases; Chapter - 11: Building skills and aligning culture; Section - THREE: Making data-driven and AI enabled HR happen; Chapter - 12: Identifying the use cases for your organization; Chapter - 13: The future of HR

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Book SynopsisCoach your organization for data-driven change and condition it to attain excellence in its data capabilities, mindset and performance with this guide for data leaders.

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Book SynopsisJordan Morrow is known as the "Godfather of Data Literacy", having helped pioneer the field by building one of the world's first data literacy programs. He is the founder and CEO of Bodhi Data and the Senior Vice President of Data and AI Transformation for AgileOne. He served as the Chair of the Advisory Board for The Data Literacy Project and has helped companies and organizations around the world, including the United Nations, build and understand data literacy. Morrow is the author of three other books: Be Data Literate, Be Data Driven and Be Data Analytical all published by Kogan Page.

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Book SynopsisBowei Chen is Associate Professor of Marketing Analytics and Data Science at the Adam Smith Business School, University of Glasgow, UK. He is also the Programme Director of the MSc in Finance and Management and an ESRC IAA Reviewer. Gerhard Kling is Professor in Finance at the University of Aberdeen, UK. He has worked in higher education for over 18 years (SOAS, University of Southampton, UWE, Utrecht University).

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Book SynopsisBowei Chen is Associate Professor of Marketing Analytics and Data Science at the Adam Smith Business School, University of Glasgow, UK. He is also the Programme Director of the MSc in Finance and Management and an ESRC IAA Reviewer. Gerhard Kling is Professor in Finance at the University of Aberdeen, UK. He has worked in higher education for over 18 years (SOAS, University of Southampton, UWE, Utrecht University).

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Book SynopsisHani Nabeel is the Chief Behavioural Scientist at iPsychTec, a people analytics and behavioural science company. He has over 20 years' experience in talent management consulting and quantitative behavioural research. He is an in-demand conference speaker and industry writer on all aspects of culture measurement, people analytics and behavioural science. He is based in London, UK.

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Book SynopsisJordan Morrow is known as the "Godfather of Data Literacy", having helped pioneer the field by building one of the world's first data literacy programs. He is the founder and CEO of Bodhi Data and the Senior Vice President of Data and AI Transformation for AgileOne, helping to utilize data and AI in the total talent management space. He served as the Chair of the Advisory Board for The Data Literacy Project and has helped companies and organizations around the world, including the United Nations, build and understand data literacy. Morrow is the author of four books: Be Data Literate, Be Data Driven, Be Data Analytical, and Business 101 for the Data Professional all published by Kogan Page. He is based near Salt Lake City, Utah.

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