Cover for Principles of Big Data

Principles of Big Data

Preparing, Sharing, and Analyzing Complex Information

Book2013

Author:

Jules J. Berman

Principles of Big Data

Preparing, Sharing, and Analyzing Complex Information

Book2013

 

Cover for Principles of Big Data

Author:

Jules J. Berman

About the book

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Book description

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 orga ... read full description

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  2. Book chapterAbstract only

    Chapter 1 - Providing Structure to Unstructured Data

    Pages 1-14

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    Chapter 2 - Identification, Deidentification, and Reidentification

    Pages 15-33

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    Chapter 3 - Ontologies and Semantics

    Pages 35-48

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    Chapter 4 - Introspection

    Pages 49-61

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    Chapter 5 - Data Integration and Software Interoperability

    Pages 63-75

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    Chapter 6 - Immutability and Immortality

    Pages 77-87

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    Chapter 7 - Measurement

    Pages 89-98

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    Chapter 8 - Simple but Powerful Big Data Techniques

    Pages 99-127

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    Chapter 9 - Analysis

    Pages 129-144

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    Chapter 10 - Special Considerations in Big Data Analysis

    Pages 145-155

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    Chapter 11 - Stepwise Approach to Big Data Analysis

    Pages 157-165

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    Chapter 12 - Failure

    Pages 167-182

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    Chapter 13 - Legalities

    Pages 183-199

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    Chapter 14 - Societal Issues

    Pages 201-215

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    Chapter 15 - The Future

    Pages 217-227

  17. Book chapterNo access

    Glossary

    Pages 229-245

  18. Book chapterNo access

    References

    Pages 247-255

  19. Book chapterNo access

    Index

    Pages 257-261

About the book

Description

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 endowed with semantic support (i.e., organized in classes of uniquely identified data objects). Readers will learn how their data can be integrated with data from other resources, and how the data extracted from Big Data resources can be used for purposes beyond those imagined by the data creators.

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 endowed with semantic support (i.e., organized in classes of uniquely identified data objects). Readers will learn how their data can be integrated with data from other resources, and how the data extracted from Big Data resources can be used for purposes beyond those imagined by the data creators.

Key Features

  • Learn general methods for specifying Big Data in a way that is understandable to humans and to computers
  • Avoid the pitfalls in Big Data design and analysis
  • Understand how to create and use Big Data safely and responsibly with a set of laws, regulations and ethical standards that apply to the acquisition, distribution and integration of Big Data resources
  • Learn general methods for specifying Big Data in a way that is understandable to humans and to computers
  • Avoid the pitfalls in Big Data design and analysis
  • Understand how to create and use Big Data safely and responsibly with a set of laws, regulations and ethical standards that apply to the acquisition, distribution and integration of Big Data resources

Details

ISBN

978-0-12-404576-7

Language

English

Published

2013

Copyright

Copyright © 2013 Elsevier Inc. All rights reserved.

Imprint

Morgan Kaufmann

Authors

Jules J. Berman