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Principles of Big Data
Preparing, Sharing, and Analyzing Complex Information
Learn simple, but powerful methods that permit data to be shared and integrated among different big Data resources
Jules J. Berman (Author)
9780124045767
Paperback, published 4 July 2013
288 pages
23.4 x 19 x 1.9 cm, 0.58 kg
"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." --ODBMS.org, March 2014 "The book is written in a colloquial style and is full of anecdotes, quotations from famous people, and personal opinions." --ComputingReviews.com, February 2014 "The author has produced a sober, serious treatment of this emerging phenomenon, avoiding hype and gee-whiz cases in favor of concepts and mature advice. For example, the author offers ten distinctions between big data and small data, including such factors as goals, location, data structure, preparation, and longevity. This characterization provides much greater insight into the phenomenon than the standard 3V treatment (volume, velocity, and variety)." --ComputingReviews.com, October 2013
Approx.262 pages
1. Big Data Moves to the Center of the Universe 2. Measurement 3. Annotation 4. Identification, De-identification, and Re-identification 5. Ontologies and Semantics: How information is endowed with meaning 6. Standards and their Versions 7. Legacy Data 8. Hypothesis Testing 9. Prediction 10. Software 11. Complexity 12. Vulnerabilities 13. Legalities 14. Social and Ethical Issues
