Database design and theory Books
Manning Publications Kafka in Action
Book SynopsisKafka in Action is a practical, hands-on guide to building Kafka-based data pipelines. Filled with real-world use cases and scenarios, this book probes Kafka's most common use cases, ranging from simple logging through managing streaming data systems for message routing, analytics, and more. In systems that handle big data, streaming data, or fast data, it's important to get your data pipelines right. Apache Kafka is a wicked-fast distributed streaming platform that operates as more than just a persistent log or a flexible message queue. Key Features · Understanding Kafka's concepts · Implementing Kafka as a message queue · Setting up and executing basic ETL tasks · Recording and consuming streaming data · Working with Kafka producers and consumers from Java applications · Using Kafka as part of a large data project team · Performing Kafka developer and admin tasks Written for intermediate Java developers or data engineers. No prior knowledge of Kafka is required. About the technology Apache Kafka is a distributed streaming platform for logging and streaming data between services or applications. With Kafka, it's easy to build applications that can act on or react to data streams as they flow through your system. Operational data monitoring, large scale message processing, website activity tracking, log aggregation, and more are all possible with Kafka. Dylan Scott is a software developer with over ten years of experience in Java and Perl. His experience includes implementing Kafka as a messaging system for a large data migration, and he uses Kafka in his work in the insurance industry.
£33.99
O'Reilly Media Automating Data Quality Monitoring at Scale
Book SynopsisIn this book, Jeremy Stanley and Paige Schwartz from Anomalo explain how you can use automated data quality monitoring to cover all your tables efficiently, proactively alert on every category of issue, and resolve problems immediately.
£39.74
O'Reilly Media Python Data Science Handbook
Book SynopsisWorking scientists and data crunchers familiar with reading and writing Python code will find the second edition of this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models.
£47.99
O'Reilly Media Deciphering Data Architectures
Book SynopsisData fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. These new architectures have solid benefits, but they're also surrounded by a lot of hyperbole and confusion. This practical book provides a guided tour of each architecture to help data professionals understand its pros and cons.
£47.99
Atlantic Books The Hidden Half: The Unseen Forces That Influence
Book SynopsisWhy does one smoker die of lung cancer but another live to 100? The answer is 'The Hidden Half' - those random, unknowable variables that mess up our attempts to comprehend the world.We humans are very clever creatures - but we're idiots about how clever we really are. In this entertaining and ingenious book, Blastland reveals how in our quest to make the world more understandable, we lose sight of how unexplainable it often is. The result - from GDP figures to medicine - is that experts know a lot less than they think. Filled with compelling stories from economics, genetics, business, and science, The Hidden Half is a warning that an explanation which works in one arena may not work in another. Entertaining and provocative, it will change how you view the world.Trade ReviewHighly original and challenging... Once you have read this book, you can't unread it. * Daniel Finkelstein, The Times *Fascinating and provocative. Blastland is one of the most original thinkers around. * Tim Harford - Financial Times columnist and author of The Undercover Economist *Elegantly written and mind-expanding, The Hidden Half will enthrall you with its storytelling while educating you with its scientific depth. * Daniel H. Pink - bestselling author of Drive *Brilliant. Blastland provides an explanation of the need for humility in the face of the inevitable limits to knowledge and our all-too-human temptation to tell stories about the world that go far beyond what the evidence will support. * Diane Coyle - Bennett Professor of Public Policy, Cambridge University *Fascinating... As John Wooden said, it's what you learn after you know it all that counts. * Andrew Gelman - author of Rich State Poor State Red State Blue State *Excellent. Blastland makes a compelling case that God is fond of playing dice with the cosmos-and the list of unpredictable things keeps growing, not shrinking. * Phillip Tetlock - bestselling author of Superforecasting *Beautifully written and often very funny. Anyone making decision that matter should enjoy this book and profit from its lessons. * Dame Frances Cairncross - Chair, Executive Committee of the Institute for Fiscal Studies *Thought-provoking. * UnHerd *Table of Contents0: Prologue 1: Bill is not Ben 2: I am not constant 3: Here is not there, now is not then 4: One path is not enough 5: The principle isn't practical 6: Big is not small 7: Big is not clear 8: The ignorant chicken 9: What to do 10: Postscript
£10.44
O'Reilly Media Data Modeling with Microsoft Power BI
Book Synopsis
£44.79
O'Reilly Media Scaling Python with Dask
Book SynopsisWith this short but thorough resource, data scientists and Python programmers will learn how the Dask open source library for parallel computing provides APIs that make it easy to parallelize PyData libraries including NumPy, pandas, and scikit-learn.
£47.99
O'Reilly Media Kafka Connect
Book SynopsisWith this practical guide, authors Mickael Maison and Kate Stanley show data engineers, site reliability engineers, and application developers how to build data pipelines between Kafka clusters and a variety of data sources and sinks.
£47.99
O'Reilly Media Delta Lake Up and Running
Book SynopsisWith the surge in big data and AI, organizations can rapidly create data products. However, the effectiveness of their analytics and machine learning models depends on the data's quality. Delta Lake's open source format offers a robust lakehouse framework over platforms like Amazon S3, ADLS, and GCS.
£39.74
O'Reilly Media Machine Learning and Data Science Blueprints for
Book SynopsisOver the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry.
£47.99
De Gruyter Data Fabric Architectures: Web-Driven
Book SynopsisThe immense increase on the size and type of real time data generated across various edge computing platform results in unstructured databases and data silos. This edited book gathers together an international set of researchers to investigate the possibilities offered by data-fabric solutions; the volume focuses in particular on data architectures and on semantic changes in future data landscapes.
£105.00
Manning Publications Graph Databases in Action
Book SynopsisGraph Databases in Action teaches readers everything they need to know to begin building and running applications powered by graph databases. Right off the bat, seasoned graph database experts introduce readers to just enough graph theory, the graph database ecosystem, and a variety of datastores. They also explore modelling basics in action with real-world examples, then go hands-on with querying, coding traversals, parsing results, and other essential tasks as readers build their own graph-backed social network app complete with a recommendation engine! Key Features · Graph database fundamentals · An overview of the graph database ecosystem · Relational vs. graph database modelling · Querying graphs using Gremlin · Real-world common graph use cases For readers with basic Java and application development skills building in RDBMS systems such as Oracle, SQL Server, MySQL, and Postgres. No experience with graph databases is required. About the technology Graph databases store interconnected data in a more natural form, making them superior tools for representing data with rich relationships. Unlike in relational database management systems (RDBMS), where a more rigid view of data connections results in the loss of valuable insights, in graph databases, data connections are first priority. Dave Bechberger has extensive experience using graph databases as a product architect and a consultant. He’s spent his career leveraging cutting-edge technologies to build software in complex data domains such as bioinformatics, oil and gas, and supply chain management. He’s an active member of the graph community and has presented on a wide variety of graph-related topics at national and international conferences. Josh Perryman is technologist with over two decades of diverse experience building and maintaining complex systems, including high performance computing (HPC) environments. Since 2014 he has focused on graph databases, especially in distributed or big data environments, and he regularly blogs and speaks at conferences about graph databases.
£37.99
Princeton University Press Text as Data
Book SynopsisTrade Review"Among the metaverse of possible books on Text as Data that could have been published . . . I was pleased that my universe produced this one. I will assign this book as a critical part of my own course on content analysis for years to come, and it has already altered and improved the coherence of my own vocabulary and articulation for several critical choices underlying the process of turning text into data. . . . Highly recommend."---James Evans, Sociological Methods & Research
£34.20
O'Reilly Media Mastering Kafka Streams and ksqlDB
Book SynopsisWith Kafka Streams and ksqlDB, building stream processing applications is easy and fun. This practical guide shows data engineers how to use these tools to build highly scalable stream processing applications for moving, enriching, and transforming large amounts of data in real time.
£999.99
O'Reilly Media Fundamentals of Data Visualization
Book SynopsisThis practical book takes you through many commonly encountered visualization problems, and it provides guidelines on how to turn large datasets into clear and compelling figures.
£47.99
Taylor & Francis Ltd Practical Data Mining Techniques and Applications
Book SynopsisThis book focuses on how to use various data mining techniques to develop real-world applications. It offers practical applications with a clear understanding of data mining concepts. The book also has a special chapter on case studies of data mining in practice.
£50.34
Cambridge University Press Unsupervised Machine Learning for Clustering in
Book SynopsisIn the age of data-driven problem-solving, applying sophisticated computational tools for explaining substantive phenomena is a valuable skill. Yet, application of methods assumes an understanding of the data, structure, and patterns that influence the broader research program. This Element offers researchers and teachers an introduction to clustering, which is a prominent class of unsupervised machine learning for exploring and understanding latent, non-random structure in data. A suite of widely used clustering techniques is covered in this Element, in addition to R code and real data to facilitate interaction with the concepts. Upon setting the stage for clustering, the following algorithms are detailed: agglomerative hierarchical clustering, k-means clustering, Gaussian mixture models, and at a higher-level, fuzzy C-means clustering, DBSCAN, and partitioning around medoids (k-medoids) clustering.Table of Contents1. Introduction; 2. Setting the stage for clustering; 3. Agglomerative hierarchical clustering; 4. k-means clustering; 5. Gaussian mixture models; 6. Advanced methods; 7. Conclusion.
£17.00
O'Reilly Media Data Science with Java
Book SynopsisData Science is booming thanks to R and Python, but Java brings the robustness, convenience, and ability to scale critical to today's data science applications. With this practical book, Java software engineers looking to add data science skills will take a logical journey through the data science pipeline. Author Michael Brzustowicz explains the basic math theory behind each step of the data science process, as well as how to apply these concepts with Java. You'll learn the critical roles that data IO, linear algebra, statistics, data operations, learning and prediction, and Hadoop MapReduce play in the process. Throughout this book, you'll find code examples you can use in your applications. Examine methods for obtaining, cleaning, and arranging data into its purest formUnderstand the matrix structure that your data should takeLearn basic concepts for testing the origin and validity of dataTransform your data into stable and usable numerical valuesUnderstand supervised and unsupe
£35.99
BCS Learning & Development Limited Principles of Data Management: Facilitating
Book SynopsisData is a valuable corporate asset and its effective management is vital to an organisation’s success and survival. With this book you will learn to master the key principles of data management and use them to implement best practices in your organization. This professional guide covers all the key areas of data management, including database development and corporate data modelling. It is business-focused, providing the knowledge and techniques required to successfully implement the data management function. This fully updated new edition provides new chapters on the most important data topics such as big data, artificial intelligence, linked data and concept systems. Principles of Data Management is fully aligned with syllabus for the BCS Professional Certificate in Data Management Essentials, making this the go-to text to unlocking the value of your data. Ideal for business managers and all involved in the development of information systems as well as data management professionals Comprehensive and descriptive view of data management Suitable for all levels, from beginners to advanced learners Must-read for anyone involved in the development of systems to manage data Trade ReviewThis book is an excellent guide to understanding data management theory and techniques. It works at all levels: from beginner to advanced, and from reference source to the practicalities of implementation. I would highly recommend to anyone wanting to get to grips with data management, regardless of experience in the field. -- Ian Wallis, Managing Director, Data Strategists LtdKeith has developed a broad and thorough understanding of all aspects of data management over many years, so is without doubt one of the authorities on data management. This updated book includes reference to a number of new techniques as well as refining existing guidance on data modelling and database structures. Keith clearly explains both the importance of planning and analysis of databases and repositories and an explanation of key techniques to achieve this. A ‘must buy’ for the bookshelf of any data management practitioner. -- Julian Schwarzenbach, Chair of the BCS Data Management Specialist GroupThis book provides a comprehensive and descriptive view of data management within a database setting. This is a must read for anyone involved in the development of systems to manage data. This book is as useful as it is interesting. It covers everything you need to know about getting the most out of your data management processes and architecture. -- Ian Rush, Data & Process Advantage LtdTable of ContentsPart 1: Preliminaries Chapter 1 Data and the enterprise Chapter 2 Databases and their development Chapter 3 What is data management? Part 2: Data Administration Chapter 4 Corporate data modelling Chapter 5 Data definition and naming Chapter 6 Metadata Chapter 7 Data quality Chapter 8 Data accessibility Chapter 9 Master data management Part 3: Database and Repository Administration Chapter 10 Database administration Chapter 11 Repository administration Part 4: The Data Management Environment Chapter 12 The use of packaged application software Chapter 13 Distributed data and databases Chapter 14 Business intelligence Chapter 15 Object orientation Chapter 16 Multimedia Chapter 17 Integrating data and web technology Chapter 18 Linked data Chapter 19 Concept systems Chapter 20 Big data and artificial intelligence Appendices Appendix A Comparison of data modelling notations Appendix B Generic data models Appendix C HTML and XML Appendix D Techniques and skills for data management Appendix E Data strategy Appendix F International standards for data management Appendix G The BCS Data Management Essentials syllabus
£33.24
Packt Publishing Limited Python: Advanced Predictive Analytics: Gain
Book SynopsisGain practical insights by exploiting data in your business to build advanced predictive modeling applications Key Features A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices Learn how to use popular predictive modeling algorithms such as Linear Regression, Decision Trees, Logistic Regression, and Clustering Master open source Python tools to build sophisticated predictive models Book Description Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form; it needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Using the Python programming language, analysts can use these sophisticated methods to build scalable analytic applications. This book is your guide to getting started with predictive analytics using Python. You'll balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and NumPy. Through case studies and code examples using popular open-source Python libraries, this book illustrates the complete development process for analytic applications. Covering a wide range of algorithms for classification, regression, clustering, as well as cutting-edge techniques such as deep learning, this book illustrates explains how these methods work. You will learn to choose the right approach for your problem and how to develop engaging visualizations to bring to life the insights of predictive modeling. Finally, you will learn best practices in predictive modeling, as well as the different applications of predictive modeling in the modern world. The course provides you with highly practical content from the following Packt books: 1. Learning Predictive Analytics with Python 2. Mastering Predictive Analytics with Python What you will learn Understand the statistical and mathematical concepts behind predictive analytics algorithms and implement them using Python libraries Get to know various methods for importing, cleaning, sub-setting, merging, joining, concatenating, exploring, grouping, and plotting data with pandas and NumPy Master the use of Python notebooks for exploratory data analysis and rapid prototyping Get to grips with applying regression, classification, clustering, and deep learning algorithms Discover advanced methods to analyze structured and unstructured data Visualize the performance of models and the insights they produce Ensure the robustness of your analytic applications by mastering the best practices of predictive analysis Who this book is for This book is designed for business analysts, BI analysts, data scientists, or junior level data analysts who are ready to move on from a conceptual understanding of advanced analytics and become an expert in designing and building advanced analytics solutions using Python. If you are familiar with coding in Python (or some other programming/statistical/scripting language) but have never used or read about predictive analytics algorithms, this book will also help you.Table of ContentsTable of Contents Module 1 Module 2
£75.04
Packt Publishing Limited Alteryx Designer Cookbook: Over 60 recipes to
Book SynopsisStreamline your workflow, transform raw data into actionable insights, and use Alteryx Designer to shape, design, and visualize data Key Features Acquire the skills necessary to perform analytics operations like an expert Discover hidden trends and insights in your data from various sources to make accurate predictions Reduce the time and effort required to derive insights from your data Purchase of the print or Kindle book includes a free eBook in the PDF format Book DescriptionAlteryx allows you to create data manipulation and analytic workflows with a simple, easy-to-use, code-free UI, and perform fast-executing workflows, offering multiple ways to achieve the same results. The Alteryx Designer Cookbook is a comprehensive guide to maximizing your Alteryx skills and determining the best ways to perform data operations. This book's recipes will guide you through an analyst's complete journey, covering all aspects of the data life cycle. The first set of chapters will teach you how to read data from various sources to obtain reports and pass it through the required adjustment operations for analysis. After an explanation of the Alteryx platform components with a particular focus on Alteryx Designer, you’ll be taken on a tour of what and how you can accomplish by using this tool. Along the way, you’ll learn best practices and design patterns. The book also covers real-world examples to help you apply your understanding of the features in Alteryx to practical scenarios. By the end of this book, you’ll have enhanced your proficiency with Alteryx Designer and an improved ability to execute tasks within the tool efficiently.What you will learn Speed up the cleansing, data preparing, and shaping process Perform operations and transformations on the data to suit your needs Blend different types of data sources for analysis Pivot and un-pivot the data for easy manipulation Perform aggregations and calculations on the data Encapsulate reusable logic into macros Develop high-quality, data-driven reports to improve consistency Who this book is forThis book is for data analysts, data professionals, and business intelligence professionals seeking to harness the full potential of the tool. A basic understanding of Alteryx Designer and Alteryx terminology, including macros, apps, and workflows, is all you need to get started with this book.Table of ContentsTable of Contents Input data from files Working with databases Data Preparation Data Transformations Data Parsing Grouping Data Blending and Merging data Aggregations Dynamic Operations/ Tools Macros and Apps Downloads, APIs & Web Services Developer options Reporting with Alteryx Outputting Data
£48.59
Packt Publishing Limited Data Visualization a successful design process
Book SynopsisA comprehensive yet quick guide to the best approaches to designing data visualizations, with real examples and illustrative diagrams. Whatever the desired outcome ensure success by following this expert design process. This book is for anyone who has responsibility for, or is interested in trying to find innovative and effective ways to visually analyze and communicate data. There is no skill, no knowledge and no role-based pre-requisites or expectations of anyone reading this book.
£22.79
Independently Published ChatGPT on Physics: Exploring the Foundations and
Book Synopsis
£15.79
O'Reilly Media Redis Cookbook
Book SynopsisRedis is an open source, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets. This book will provide developers with problem and solutions in our useful cookbook style. This is example driven ebook.
£14.39
Basic Books The Art of Statistics: How to Learn from Data
Book Synopsis
£18.69
AU Press Open Data Structures: An Introduction
Book SynopsisOffered as an introduction to the field of data structures andalgorithms, Open Data Structures covers the implementation andanalysis of data structures for sequences (lists), queues, priorityqueues, unordered dictionaries, ordered dictionaries, and graphs.Focusing on a mathematically rigorous approach that is fast, practical,and efficient, Morin clearly and briskly presents instruction alongwith source code. Analyzed and implemented in Java, the data structures presented inthe book include stacks, queues, deques, and lists implemented asarrays and linked-lists; space-efficient implementations of lists; skiplists; hash tables and hash codes; binary search trees includingtreaps, scapegoat trees, and red-black trees; integer searchingstructures including binary tries, x-fast tries, and y-fast tries;heaps, including implicit binary heaps and randomized meldable heaps;and graphs, including adjacency matrix and adjacency listrepresentations; and B-trees. A modern treatment of an essential computer science topic, OpenData Structures is a measured balance between classical topics andstate-of-the art structures that will serve the needs of allundergraduate students or self-directed learners.Table of ContentsAcknowledgments- xi Why This Book?- xiii 1. Introduction- 1 1.1 The Need for Efficiency- 2 1.2 Interfaces- 4 1.3 Mathematical Background- 9 1.4 The Model of Computation- 18 1.5 Correctness, Time Complexity, and Space Complexity- 19 1.6 Code Samples- 22 1.7 List of Data Structures- 22 1.8 Discussion and Exercises- 26 2. Array-Based Lists- 29 2.1 ArrayStack: Fast Stack Operations Using an Array- 30 2.2 FastArrayStack: An Optimized ArrayStack- 35 2.3 ArrayQueue: An Array-Based Queue- 36 2.4 ArrayDeque: Fast Deque Operations Using an Array- 40 2.5 DualArrayDeque: Building a Deque from Two Stacks- 43 2.6 RootishArrayStack: A Space-Efficient Array Stack- 49 2.7 Discussion and Exercises- 59 3. Linked Lists- 63 3.1 SLList: A Singly-Linked List- 63 3.2 DLList: A Doubly-Linked List- 67 3.3 SEList: A Space-Efficient Linked List- 71 3.4 Discussion and Exercises- 82 4. Skiplists- 87 4.1 The Basic Structure- 87 4.2 SkiplistSSet: An Efficient Sset- 90 4.3 SkiplistList: An Efficient Random-Access List- 93 4.4 Analysis of Skiplists- 98 4.5 Discussion and Exercises- 102 5. Hash Tables- 107 5.1 ChainedHashTable: Hashing with Chaining- 107 5.2 LinearHashTable: Linear Probing- 114 5.3 Hash Codes- 122 5.4 Discussion and Exercises- 128 6. Binary Trees- 133 6.1 BinaryTree: A Basic Binary Tree- 135 6.2 BinarySearchTree: An Unbalanced Binary Search Tree- 140 6.3 Discussion and Exercises- 147 7. Random Binary Search Trees- 153 7.1 Random Binary Search Trees- 153 7.2 Treap: A Randomized Binary Search Tree- 159 7.3 Discussion and Exercises- 168 8. Scapegoat Trees- 173 8.1 ScapegoatTree: A Binary Search Tree with Partial Rebuilding-173 8.2 Discussion and Exercises- 181 9. Red-Black Trees- 185 9.1 2-4 Trees- 186 9.2 RedBlackTree: A Simulated 2-4 Tree- 190 9.3 Summary- 205 9.4 Discussion and Exercises- 206 10. Heaps- 211 10.1 BinaryHeap: An Implicit Binary Tree- 211 10.2 MeldableHeap: A Randomized Meldable Heap- 217 10.3 Discussion and Exercises- 222 11. Sorting Algorithms- 225 11.1 Comparison-Based Sorting- 226 11.2 Counting Sort and Radix Sort- 238 11.3 Discussion and Exercises- 243 12. Graphs- 247 12.1 AdjacencyMatrix: Representing a Graph by a Matrix- 249 12.2 AdjacencyLists: A Graph as a Collection of Lists- 252 12.3 Graph Traversal- 256 12.4 Discussion and Exercises- 261 13. Data Structures for Integers- 265 13.1 BinaryTrie: A digital search tree- 266 13.2 XFastTrie: Searching in Doubly-Logarithmic Time- 272 13.3 YFastTrie: A Doubly-Logarithmic Time SSet- 275 13.4 Discussion and Exercises- 280 14. External Memory Searching- 283 14.1 The Block Store- 285 14.2 B-Trees- 285 14.3 Discussion and Exercises- 304 Bibliography- 309 Index- 317
£25.19
Machine Learning
Book Synopsis
£999.99
O'Reilly Media Tableau Desktop Pocket Reference
Book SynopsisIn a crowded field of data visualization and analytics tools, Tableau Desktop has emerged as the clear leader. With this handy pocket reference, author Ryan Sleeper (Innovative Tableau) shows you how to translate the vast amounts of data into useful information.
£28.95
Nova Science Publishers Inc Data Storage: Systems, Management & Security
Book Synopsis
£83.29
Holy Macro! Books Supercharge Power BI: Power BI is Better When You
Book SynopsisData analysis expressions (DAX) is the formula language of Power BI. Learning the DAX language is key to empower Power BI users so they can take advantage of these new Business Intelligence (BI) capabilities. This third edition has been updated for the new Power BI Ribbon interface while still providing a bridge for readers wanting to learn DAX in the Power BI, Power Pivot, or Excel.
£26.31
Technics Publications LLC Data Modeling Master Class Training Manual: Steve
Book Synopsis
£159.19
Technics Publications LLC Object-Role Modeling Workbook: Data Modeling
Book SynopsisObject-Role Modeling (ORM) is a fact-based approach to data modelling that expresses the information requirements of any business domain simply in terms of objects that play roles in relationships. All facts of interest are treated as instances of attribute-free structures known as fact types, where the relationship may be unary (eg: Person smokes), binary (eg: Person was born on Date), ternary (eg: Customer bought Product on Date), or longer. Fact types facilitate natural expression, are easy to populate with examples for validation purposes, and have greater semantic stability than attribute-based structures such as those used in Entity Relationship Modeling (ER) or the Unified Modeling Language (UML). All relevant facts, constraints and derivation rules are expressed in controlled natural language sentences that are intelligible to users in the business domain being modelled. This allows ORM data models to be validated by business domain experts who are unfamiliar with ORM''s graphical notation. For the data modeller, ORM''s graphical notation covers a much wider range of constraints than can be expressed in industrial ER or UML class diagrams, and thus allows rich visualisation of the underlying semantics. Written as a sequel to the author''s previous book "Object-Role Modeling Fundamentals", this book briefly reviews the fundamentals of ORM, and then discusses additional topics such as model reports generation, vocabulary glossaries, relational mapping options, annotated relational schemas, schema optimisation, and data modelling patterns. Written in easy-to-understand language, it illustrates each topic with simple examples, and explains how to use the freeware NORMA tool to implement the ideas discussed. The book also includes many practical exercises to promote expertise in the techniques covered, with answers provided to all the exercise questions.
£36.89
Nova Science Publishers Inc Soft Computing: Developments, Methods &
Book Synopsis
£148.79
Technics Publications LLC Data Modeling Master Class Training Manual: Steve
Book Synopsis
£159.19
Sanderson Press, LLC Hyper Changing the way you think about plan and execute business intelligence for real results real fast
£41.40
DecisionOne Press Agile Data Warehouse Design
£27.89
£29.38
MC Press, LLC DB2 11 for z/OS Database Administration: Certification Study Guide
Book SynopsisWritten primarily for database administrators who work on z/OS and who are taking the IBM DB2 11 for z/OS Database Administration certification exam (Exam 312), this resource also appeals to those who simply want to master the skills needed to be an effective database administrator of z/OS mainframes. This study guide is designed to provide those seeking certification with an intense overview of DB2 11 for z/OS and all topics covered on the exam. Sample questions are provided at the end of each chapter, along with answers and explanations.
£68.99
Clanrye International Computational and Mathematical Modeling
£96.52
Clanrye International Data Structures and Algorithms in Computer Science
£103.72
Clanrye International Database Systems: Design, Implementation and Management
£103.50
Technics Publications MongoDB Data Modeling and Schema Design
£35.99
Technics Publications LLC The Elephant in the Fridge: Guided Steps to Data Vault Success through Building Business-Centered Models
Book SynopsisYou want the rigour of good data architecture at the speed of agile? Then this is the missing link - your step-by-step guide to Data Vault success. Success with a Data Vault starts with the business and ends with the business. Sure, theres some technical stuff in the middle, and it is absolutely essential -- but its not sufficient on its own. This book will help you shape the business perspective, and weave it into the more technical aspects of Data Vault modeling. You can read the foundational books and go on courses, but one massive risk still remains. Dan Linstedt, the founder of the Data Vault, very clearly directs those building a Data Vault to base its design on an enterprise ontology. And Hans Hultgren similarly stresses the importance of the business concepts model. So its important. We get that. But: What on earth is an enterprise ontology/business concept model, cause I wont know if Ive got one if I dont know what Im looking for? If I cant find one, how do I get my hands on such a thing? Even if I have one of these wonderful things, how do I apply it to get the sort of Data Vault thats recommended? Its actually not as hard as some would fear to answer all of these questions, and its certainly worth the effort. This book just might save you a world of pain. Its a supplement to other material on Data Vault modeling, but its the vital missing link to finding simplicity for Data Vault success.
£38.24
£30.95
AI Publishing LLC Data Science Crash Course for Beginners with Python: Fundamentals and Practices with Python
£19.60
AI Publishing LLC Python Machine Learning for Beginners: Learning from scratch NumPy, Pandas, Matplotlib, Seaborn, Scikitlearn, and TensorFlow for Machine Learning and Data Science
£17.55
Sqlbi Corp. DAX Patterns: Second Edition
£32.21
Packt Publishing Limited The Economics of Data, Analytics, and Digital Transformation: The theorems, laws, and empowerments to guide your organization's digital transformation
Book SynopsisBuild a continuously learning and adapting organization that can extract increasing levels of business, customer and operational value from the amalgamation of data and advanced analytics such as AI and Machine Learning Key Features Master the Big Data Business Model Maturity Index methodology to transition to a value-driven organizational mindset Acquire implementable knowledge on digital transformation through 8 practical laws Explore the economics behind digital assets (data and analytics) that appreciate in value when constructed and deployed correctly Book DescriptionIn today’s digital era, every organization has data, but just possessing enormous amounts of data is not a sufficient market discriminator. The Economics of Data, Analytics, and Digital Transformation aims to provide actionable insights into the real market discriminators, including an organization’s data-fueled analytics products that inspire innovation, deliver insights, help make practical decisions, generate value, and produce mission success for the enterprise. The book begins by first building your mindset to be value-driven and introducing the Big Data Business Model Maturity Index, its maturity index phases, and how to navigate the index. You will explore value engineering, where you will learn how to identify key business initiatives, stakeholders, advanced analytics, data sources, and instrumentation strategies that are essential to data science success. The book will help you accelerate and optimize your company’s operations through AI and machine learning. By the end of the book, you will have the tools and techniques to drive your organization’s digital transformation. Here are a few words from Dr. Kirk Borne, Data Scientist and Executive Advisor at Booz Allen Hamilton, about the book: "Data analytics should first and foremost be about action and value. Consequently, the great value of this book is that it seeks to be actionable. It offers a dynamic progression of purpose-driven ignition points that you can act upon."What you will learn Train your organization to transition from being data-driven to being value-driven Navigate and master the big data business model maturity index Learn a methodology for determining the economic value of your data and analytics Understand how AI and machine learning can create analytics assets that appreciate in value the more that they are used Become aware of digital transformation misconceptions and pitfalls Create empowered and dynamic teams that fuel your organization’s digital transformation Who this book is forThis book is designed to benefit everyone from students who aspire to study the economic fundamentals behind data and digital transformation to established business leaders and professionals who want to learn how to leverage data and analytics to accelerate their business careers.Table of ContentsTable of Contents The CEO Mandate: Become Value-driven, Not Data-driven Value Engineering: The Secret Sauce for Data Science Success A Review of Basic Economic Concepts University of San Francisco Economic Value of Data Research Paper The Economic Value of Data Theorems The Economics of Artificial Intelligence The Schmarzo Economic Digital Asset Valuation Theorem The 8 Laws of Digital Transformation Creating a Culture of Innovation Through Empowerment Appendix A: My Most Popular Economics of Data, Analytics, and Digital Transformation Infographics Appendix B: The Economics of Data, Analytics, and Digital Transformation Cheat Sheet
£37.99
