Database design and theory Books
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.
£32.79
Nova Science Publishers Inc Soft Computing: Developments, Methods &
Book Synopsis
£148.79
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
CABI Publishing Big Data’s Big Potential in Developing Economies:
Book SynopsisBig data involves the use of sophisticated analytics to make decisions based on large-scale data inputs. It is set to transform agriculture, environmental protection and healthcare in developing countries. This book critically evaluates the developing big data industry and market in these countries and gives an overview of the determinants, performance and impacts. It provides a detailed analysis of technology creation, technology infrastructures and human skills required to utilize big data while discussing novel applications and business models that make use of it to overcome healthcare barriers. The book also offers an analysis of big data's potential to improve environmental monitoring and protection where it is likely to have far-reaching and profound impacts on the agricultural sector. A key question addressed is how gains in agricultural productivity associated with big data will benefit smallholder farmers relative to global multinationals in that sector. The book also probes big data's roles in the creation of markets that can improve the welfare of smallholder farmers. Special consideration is given to big data-led transformation of the financial industry and discusses how the transformation can increase small-holder farmers' access to finance by changing the way lenders assess creditworthiness of potential borrowers. It also takes a look at data privacy and security issues facing smallholder farmers and reviews differences in such issues in industrialized and developing countries. The key ideas, concepts and theories presented are explored, illustrated and contrasted through in-depth case studies of developing world-based big data companies, and deployment and utilization of big data in agriculture, environmental protection and healthcare.Table of ContentsChapter 1: Big Data in Developing Countries: Current Status, Opportunities and Challenges Chapter 2: Big Data Ecosystem in Developing Countries Chapter 3: Big Data in Environmental Protection and Resources Conservation Chapter 4: Big Data in Healthcare Delivery and Outcomes Chapter 5: Big Data in Agriculture Chapter 6: Big Data’s Roles in Increasing Smallholder Farmers’ Access to Finance Chapter 7: Data Privacy and Security Issues Facing Smallholder Farmers and Poor Communities in Developing Countries Chapter 8: Lessons Learned, Implications and the Way Forward
£89.09
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 Become a Python Data Analyst: Perform exploratory
Book SynopsisEnhance your data analysis and predictive modeling skills using popular Python toolsKey Features Cover all fundamental libraries for operation and manipulation of Python for data analysis Implement real-world datasets to perform predictive analytics with Python Access modern data analysis techniques and detailed code with scikit-learn and SciPy Book DescriptionPython is one of the most common and popular languages preferred by leading data analysts and statisticians for working with massive datasets and complex data visualizations.Become a Python Data Analyst introduces Python’s most essential tools and libraries necessary to work with the data analysis process, right from preparing data to performing simple statistical analyses and creating meaningful data visualizations.In this book, we will cover Python libraries such as NumPy, pandas, matplotlib, seaborn, SciPy, and scikit-learn, and apply them in practical data analysis and statistics examples. As you make your way through the chapters, you will learn to efficiently use the Jupyter Notebook to operate and manipulate data using NumPy and the pandas library. In the concluding chapters, you will gain experience in building simple predictive models and carrying out statistical computation and analysis using rich Python tools and proven data analysis techniques.By the end of this book, you will have hands-on experience performing data analysis with Python.What you will learn Explore important Python libraries and learn to install Anaconda distribution Understand the basics of NumPy Produce informative and useful visualizations for analyzing data Perform common statistical calculations Build predictive models and understand the principles of predictive analytics Who this book is forBecome a Python Data Analyst is for entry-level data analysts, data engineers, and BI professionals who want to make complete use of Python tools for performing efficient data analysis. Prior knowledge of Python programming is necessary to understand the concepts covered in this bookTable of ContentsTable of Contents The Anaconda Distribution and Jupyter Notebook Vectorizing Operations with Numpy Pandas: Everyone’s Favorite Data Analysis Library Visualization and Exploratory Data Analysis Statistical Computing with Python Introduction to Predictive Analytics Models
£18.99
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
ISTE Ltd and John Wiley & Sons Inc From Big Data to Smart Data
Book SynopsisA pragmatic approach to Big Data by taking the reader on a journey between Big Data (what it is) and the Smart Data (what it is for). Today’s decision making can be reached via information (related to the data), knowledge (related to people and processes), and timing (the capacity to decide, act and react at the right time). The huge increase in volume of data traffic, and its format (unstructured data such as blogs, logs, and video) generated by the “digitalization” of our world modifies radically our relationship to the space (in motion) and time, dimension and by capillarity, the enterprise vision of performance monitoring and optimization.Table of ContentsPREFACE ix LIST OF FIGURES AND TABLES xiii INTRODUCTION xv CHAPTER 1. WHAT IS BIG DATA? 1 1.1. The four “V”s characterizing Big Data 3 1.1.1. V for “Volume” 3 1.1.2. V for “Variety” 4 1.1.3. V for “Velocity” 8 1.1.4. V for “Value”, associated with Smart Data 9 1.2. The technology that supports Big Data 10 CHAPTER 2. WHAT IS SMART DATA? 13 2.1. How can we define it? 13 2.1.1. More formal integration into business processes 13 2.1.2. A stronger relationship with transaction solutions 14 2.1.3. The mobility and the temporality of information 15 2.2. The structural dimension 17 2.2.1. The objectives of a BICC 17 2.3. The closed loop between Big Data and Smart Data 18 CHAPTER 3. ZERO LATENCY ORGANIZATION 21 3.1. From Big Data to Smart Data for a zero latency organization 21 3.2. Three types of latency 21 3.2.1. Latency linked to data 21 3.2.2. Latency linked to analytical processes 22 3.2.3. Latency linked to decisionmaking processes 23 3.2.4. Action latency 23 CHAPTER 4. SUMMARY BY EXAMPLE 25 4.1. Example 1: date/product/price recommendation 26 4.1.1. Steps “1” and “2” 28 4.1.2. Steps “3” and “4”: enter the world of “Smart Data” 29 4.1.3. Step “5”: the presentation phase 29 4.1.4. Step “6”: the “Holy Grail” (the purchase) 30 4.1.5. Step “7”: Smart Data 30 4.2. Example 2: yield/revenue management (rate controls) 31 4.2.1. How it works: an explanation based on the Tetris principle (see Figure 4.4) 35 4.3. Example 3: optimization of operational performance 38 4.3.1. General department (top management) 42 4.3.2. Operations departments (middle management) 42 4.3.3. Operations management (and operational players) 43 CONCLUSION 47 BIBLIOGRAPHY 51 GLOSSARY 53 INDEX 57
£125.06
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
Technics Publications LLC Data Modeling Master Class Training Manual: Steve
Book Synopsis
£149.24
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
Springer Fachmedien Wiesbaden Einführung in Evolutionäre Algorithmen:
Book SynopsisDieses Lehrbuch aus dem KI-Themenfeld richtet sich an Wirtschaftsinformatiker und Informatiker, ferner an Ingenieure und OR-Spezialisten. Es bietet eine umfassende methodisch orientierte Einführung in das Optimieren mit Evolutionären Algorithmen. Dazu gehören vor allem Genetische Algorithmen, Evolutionsstrategien, Genetische bzw. Evolutionäre Programmierung. Wichtige Ergebnisse der Theorie werden in gut verständlicher Form wiedergegeben. Zahlreiche Abbildungen und Beispiele sowie Hinweise auf Quellen im Internet und Testdaten ergänzen den Text. Das Buch kann als Grundlage zur Entwicklung eigener Anwendungen dienen oder als begleitender Text für Lehrveranstaltungen.Table of ContentsThematische Einordnung - Relevante Grundelemente der Evolutionstheorie - Genetische Algorithmen - Genetische Programmierung - Evolutionsstrategien - Evolutionäre Programmierung - Lernende Classifier Systeme - Kombinationsmöglichkeiten mit Neuronalen Netzen und der Fuzzy Set Theorie - Vergleich und Beurteilung von Evolutionären Algorithmen - Zahlreiche Abbildungen und Beispiele - Umfangreiche Literaturhinweise - Verweise auf Quellen im Internet - Testdaten - Index
£34.19
Springer Fachmedien Wiesbaden Ordnungen und Verbände: Grundlagen,
Book SynopsisDas Lehrbuch stellt eine grundlegende Einführung in die mathematische Theorie der geordneten Mengen und Verbände dar. Neben wichtigen Begriffen werden allgemeine Vorgehensweisen und Beweistechniken demonstriert, die für dieses Gebiet typisch sind. Auch werden eine Reihe von Anwendungen diskutiert, insbesondere aus der Informatik, wie logische Schaltungen, Semantik von Programmiersprachen und die Untersuchung von Kausalität in verteilten Systemen.Table of ContentsMathematische Grundlagen - Verbände und Ordnungen - Einige wichtige Verbandsklassen - Fixpunkttheorie mit Anwendungen - Vervollständigung und Darstellung mittels Vervollständigung - Wohlgeordnete Mengen und das Auswahlaxiom - Einige Informatik-Anwendungen von Ordnungen und Verbänden
£34.19
Springer Fachmedien Wiesbaden SQL & NoSQL Databases: Models, Languages,
Book SynopsisThis book offers a comprehensive introduction to relational (SQL) and non-relational (NoSQL) databases. The authors thoroughly review the current state of database tools and techniques, and examine coming innovations. The book opens with a broad look at data management, including an overview of information systems and databases, and an explanation of contemporary database types: SQL and NoSQL databases, and their respective management systems The nature and uses of Big Data A high-level view of the organization of data management Data Modeling and Consistency Chapter-length treatment is afforded Data Modeling in both relational and graph databases, including enterprise-wide data architecture, and formulas for database design. Coverage of languages extends from an overview of operators, to SQL and and QBE (Query by Example), to integrity constraints and more. A full chapter probes the challenges of Ensuring Data Consistency, covering: Multi-User Operation Troubleshooting Consistency in Massive Distributed Data Comparison of the ACID and BASE consistency models, and more System Architecture also gets from its own chapter, which explores Processing of Homogeneous and Heterogeneous Data; Storage and Access Structures; Multi-dimensional Data Structures and Parallel Processing with MapReduce, among other topics. Post-Relational and NoSQL Databases The chapter on post-relational databases discusses the limits of SQL – and what lies beyond, including Multi-Dimensional Databases, Knowledge Bases and and Fuzzy Databases. A final chapter covers NoSQL Databases, along with Development of Non-Relational Technologies, Key-Value, Column-Family and Document Stores XML Databases and Graphic Databases, and more The book includes more than 100 tables, examples and illustrations, and each chapter offers a list of resources for further reading. SQL & NoSQL Databases conveys the strengths and weaknesses of relational and non-relational approaches, and shows how to undertake development for big data applications. The book benefits readers including students and practitioners working across the broad field of applied information technology.This textbook has been recommended and developed for university courses in Germany, Austria and Switzerland.Table of ContentsData Management - Data Modeling - Database Languages - Ensuring Data Consistency - System Architecture - Post-Relational Databases - NoSQL Databases
£40.49
Springer Fachmedien Wiesbaden Algorithmen und Datenstrukturen
Book SynopsisStatt der üblichen theoretischen Zugangs vermittelt dieses Lehrbuch Algorithmen und Datenstrukturen durch die Geschichte einer jungen Informatikerin. Der Stoff einer traditionellen Einführungsveranstaltung Informatik wird so ausgehend von der praktischen Anwendung lebendig und mit viel Spaß vermittelt. So schlägt das Buch eine Brücke von Alltagserfahrungen zu den Konzepten von Datenstrukturen und Algorithmen. Table of ContentsEin Anwendungsbeispiel - Machbarkeit und Effizienz - Einfache Ansätze - Verbesserung durch mehr Struktur - Gierige Algorithmen - Kleinster Schaden im Worst-Case - Teile und Beherrsche - Dynamisches Programmieren - Direkter Zugriff - Prioritätswarteschlangen - Extern gespeicherte Daten - Selbstorganisation - Zusammenfassung
£29.99
Independently Published ChatGPT on Physics: Exploring the Foundations and
Book Synopsis
£15.79
