Databases / Data management Books

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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Book SynopsisBusiness operations in large organizations today involve massive, interactive, and layered networks of teams and personnel collaborating across hierarchies and countries on complex tasks. To optimize productivity, businesses need to know: what communication patterns do high-performing teams have in common? Is it possible to predict a team''s performance before it starts work on a project? How can productive team behavior be fostered? This comprehensive review for researchers and practitioners in data mining and social networks surveys recent progress in the emerging field of network science of teams. Focusing on the underlying social network structure, the authors present models and algorithms characterizing, predicting, optimizing, and explaining team performance, along with key applications, open challenges, and future trends.Trade Review'This is a timely book for team science, with a unique perspective that uses computational approaches to study the network effect on team performance. The book has a nice balance of theory, algorithms, and empirical studies. The authors possess years of experience in the field.' Charu Aggarwal, IBM Research AI'A comprehensive study that pushes forward our understanding of and ability to forecast and design team performance - a critical, yet complex human-subject phenomenon to which this book brings in-depth technical rigor.' Leman Akoglu, Carnegie Mellon University'This pioneering book is essential to technologists, data scientists, and researchers alike, offering a modern, computational approach to the science of teaming and how to manage the convergence of people, information, and technology in networked organizations.' Norbou Buchler, US Army Data and Analysis Center'Li and Tong have provided a thorough and insightful exploration of current research on teams in networks, linking computational techniques with results from the social sciences. A pleasure to read.' Sucheta Soundarajan, Syracuse University'This brief volume is a valuable resource for managers, but managers with a strong background in data science, and for other technologists involved in designing systems that support user interactions … The added value of this book is provided by the mathematical formalisms used, which encode characteristics of the computational challenges discussed … The topical focus results in a unique volume that might lead interested readers to discover new research avenues … Recommended' J. Brzezinski, ChoiceTable of Contents1. Introduction; 2. Team performance characterization; 3. Team performance prediction; 4. Team performance optimization; 5. Team performance explanation; 6. Human agent teaming; 7. Conclusion and future work.

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Book SynopsisIntroducing SQLite.- Getting Started.- SQL for SQLite.- Advanced SQL for SQLite.- SQLite Design and Concepts.- The Core C API.- The Extension C API.- Language Extensions.- iOS Development with SQLite.- Android Development with SQLite.- SQLite Internals and New Features.Table of Contents Introducing SQLite Getting Started SQL for SQLite Advanced SQL for SQLite SQLite Design and Concepts The Core C API The Extension C API Language Extensions iOS Development with SQLite Android Development with SQLite SQLite Internals and New Features

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Book SynopsisBeginning Oracle SQL is your introduction to the interactive query tools and specific dialect of SQL used with Oracle Database.Table of Contents1. Relational Database Systems and Oracle2. Introduction to SQL and SQL*Plus, and SQL Developer3. Data Definition, Part I4. Retrieval: The Basics5. Retrieval: Functions6. Data Manipulation7. Data Definition, Part II8. Retrieval: Joins and Grouping9. Retrieval: Advanced Features10. Views11. Automating12. Object-Relational Features13. Appendix A – Case Tables14. Appendix B – Exercise Solutions

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Book SynopsisManaging and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety of important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy.Trade ReviewFrom the reviews:“This book provides a survey of some recent advances in graph mining. It contains chapters on graph languages, indexing, clustering, pattern mining, keyword search, and pattern matching. … The book is targeted at advanced undergraduate or graduate students, faculty members, and researchers from both industry and academia. … I highly recommend this book to someone who is starting to explore the field of graph mining or wants to delve deeper into this exciting field.” (Dimitrios Katsaros, ACM Computing Reviews, December, 2010)Table of ContentsAn Introduction to Graph Data.- Graph Data Management and Mining: A Survey of Algorithms and Applications.- Graph Mining: Laws and Generators.- Query Language and Access Methods for Graph Databases.- Graph Indexing.- Graph Reachability Queries: A Survey.- Exact and Inexact Graph Matching: Methodology and Applications.- A Survey of Algorithms for Keyword Search on Graph Data.- A Survey of Clustering Algorithms for Graph Data.- A Survey of Algorithms for Dense Subgraph Discovery.- Graph Classification.- Mining Graph Patterns.- A Survey on Streaming Algorithms for Massive Graphs.- A Survey of Privacy-Preservation of Graphs and Social Networks.- A Survey of Graph Mining for Web Applications.- Graph Mining Applications to Social Network Analysis.- Software-Bug Localization with Graph Mining.- A Survey of Graph Mining Techniques for Biological Datasets.- Trends in Chemical Graph Data Mining.

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Book SynopsisChapter 1: Overview.- Chapter 2: Blogalytics.- Chapter 3: Getting Traffic for Analytics.- Chapter 4: Reviewing Performance of Campaigns.- Chapter 5: Fun with eCommerce Analytics Part I: Shopify.- Chapter 6: Fun with eCommerce Analytics Part II: AdWords.- Chapter 7: Fun with eCommerce Analytics Part III: Gumroad.- Chapter 8: Exploring Google Analytics Certification.Table of ContentsChapter 1: Overview Chapter 2: Blogalytics Chapter 3: Getting Traffic for Analytics Chapter 4: Reviewing Performance of Campaigns Chapter 5: Fun with eCommerce Analytics Part I: Shopify Chapter 6: Fun with eCommerce Analytics Part II: AdWords Chapter 7: Fun with eCommerce Analytics Part III: Gumroad Chapter 8: Exploring Google Analytics Certification

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Book SynopsisThis system-level resource specifically applies knowledge management principles, practices and technologies to the intelligence domain. Designed for those responsible for the management of an intelligence enterprise operation and its delivery of reliable intelligence to key decision-makers, the text describes the essential principles of intelligence, from collection, processing and analysis to dissemination, for both national intelligence and business applications. The author aims to provide a balanced treatment of the organizational and architectural components of knowledge management, offering an understanding of the system infrastructure, tools and technologies necessary to implement the intelligence enterprise. He explores real-world applications and presents a detailed example of competitive intelligence unit design. Including over 80 illustrations, the volume offers a practical description of enterprise architecture design methodology, and covers the full range of national, military, business and competitive intelligence.Table of ContentsKnowledge management and intelligence; the intelligence enterprise; knowledge management processes; the knowledge-based intelligence organization; intelligence analysis and synthesis; implementing analysis-synthesis; knowledge internalization and externalization; explicit knowledge combination and transformation; the intelligence enterprise architecture; knowledge management technologies.

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Book SynopsisIf you have mastered the fundamentals of the PL/SQL language and are now looking for an in-depth, practical guide to solving real problems with PL/SQL stored procedures, then this is the book for you. Table of Contents Efficient PL/SQL Package It All Up The Vexed Subject of Cursors Effective Data Handling PL/SQL Optimization Techniques Triggers DBA Packages Security Packages Web Packages PL/SQL Debugging

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Book SynopsisPro Oracle Application Express opens the "hood" of APEX and reveals the full power behind its easy-to-use GUI interface. This book shows you what you need to know to produce powerful, professionally polished applications: such as user-authentication models, approaches to layout and navigation, how to integrate Ajax, how to deal with localization issues like time zones and translations, how to customize the look and feel of an APEX web site, and more. The authors are well-qualified to write on APEX. John Scott is a hard-core APEX developer and his coauthor, Scott Spendolini, is one of the original creators of APEX.Table of ContentsA table of contents is not available for this title.

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Book SynopsisAccelerate your journey to smarter decision making by mastering the fundamentals of data literacy and developing the mindset to work confidently with dataKey Features Get a solid grasp of data literacy fundamentals to support your next steps in your career Learn how to work with data and extract meaningful insights to take the right actions Apply your knowledge to real-world business intelligence projects Book DescriptionData is more than a mere commodity in our digital world. It is the ebb and flow of our modern existence. Individuals, teams, and enterprises working with data can unlock a new realm of possibilities. And the resultant agility, growth, and inevitable success have one origin—data literacy.This comprehensive guide is written by two data literacy pioneers, each with a thorough footprint within the data and analytics commercial world and lectures at top universities in the US and the Netherlands. Complete with best practices, practical models, and real-world examples, Data Literacy in Practice will help you start making your data work for you by building your understanding of data literacy basics and accelerating your journey to independently uncovering insights.You’ll learn the four-pillar model that underpins all data and analytics and explore concepts such as measuring data quality, setting up a pragmatic data management environment, choosing the right graphs for your readers, and questioning your insights.By the end of the book, you'll be equipped with a combination of skills and mindset as well as with tools and frameworks that will allow you to find insights and meaning within your data for data-informed decision making.What you will learn Start your data literacy journey with simple and actionable steps Apply the four-pillar model for organizations to transform data into insights Discover which skills you need to work confidently with data Visualize data and create compelling visual data stories Measure, improve, and leverage your data to meet organizational goals Master the process of drawing insights, ask critical questions and action your insights Discover the right steps to take when you analyze insights Who this book is forThis book is for data analysts, data professionals, and data teams starting or wanting to accelerate their data literacy journey. If you’re looking to develop the skills and mindset you need to work independently with data, as well as a solid knowledge base of the tools and frameworks, you’ll find this book useful.Table of ContentsTable of Contents The Beginning- The Flow of Data Unfolding Your Data Journey Understanding the Four-Pillar Model Implementing Organizational Data Literacy Managing Your Data Environment Aligning with Organizational Goals Designing Dashboards and Reports Questioning the Data Handling Data Responsibly Turning Insights into Decisions Defining a Data Literacy Competency Framework Assessing Your Data Literacy Maturity Managing Data and Analytics Projects Appendix A – Templates Appendix B – References

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