Principles of Big Data. Preparing, Sharing, and Analyzing Complex Information

✍ Scribed by Jules J. Berman (Auth.)

• Publisher: Elsevier Science & Technology
• Year: 2013
• Tongue: English
• Leaves: 267
• Category: Library

✦ Synopsis

Principles of Big Data helps readers avoid the common mistakes that endanger all Big Data projects. By stressing simple, fundamental concepts, this book teaches readers how to organize large volumes of complex data, and how to achieve data permanence when the content of the data is constantly changing. General methods for data verification and validation, as specifically applied to Big Data resources, are stressed throughout the book. The book demonstrates how adept analysts can find relationships among data objects held in disparate Big Data resources, when the data objects are endo Read more...

Abstract: Principles of Big Data helps readers avoid the common mistakes that endanger all Big Data projects. By stressing simple, fundamental concepts, this book teaches readers how to organize large volumes of complex data, and how to achieve data permanence when the content of the data is constantly changing. General methods for data verification and validation, as specifically applied to Big Data resources, are stressed throughout the book. The book demonstrates how adept analysts can find relationships among data objects held in disparate Big Data resources, when the data objects are endo

✦ Table of Contents

Content:
Front Matter, Pages i-ii
Copyright, Page iv
Dedication, Page v
Acknowledgments, Page xi
Author Biography, Page xiii
Preface, Pages xv-xviii
Introduction, Pages xix-xxvi
Chapter 1 - Providing Structure to Unstructured Data, Pages 1-14
Chapter 2 - Identification, Deidentification, and Reidentification, Pages 15-33
Chapter 3 - Ontologies and Semantics, Pages 35-48
Chapter 4 - Introspection, Pages 49-61
Chapter 5 - Data Integration and Software Interoperability, Pages 63-75
Chapter 6 - Immutability and Immortality, Pages 77-87
Chapter 7 - Measurement, Pages 89-98
Chapter 8 - Simple but Powerful Big Data Techniques, Pages 99-127
Chapter 9 - Analysis, Pages 129-144
Chapter 10 - Special Considerations in Big Data Analysis, Pages 145-155
Chapter 11 - Stepwise Approach to Big Data Analysis, Pages 157-165
Chapter 12 - Failure, Pages 167-182
Chapter 13 - Legalities, Pages 183-199
Chapter 14 - Societal Issues, Pages 201-215
Chapter 15 - The Future, Pages 217-227
Glossary, Pages 229-245
References, Pages 247-255
Index, Pages 257-261