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

Morgan Kaufmann / Elsevier, 2013. — 288 p. — ISBN: 0124045766, 9780124045767Principles 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.Big Data Moves to the Center of the Universe
Measurement
Annotation
Identification, De-identification, and Re-identification
Ontologies and Semantics: How information is endowed with meaning
Standards and their Versions
Legacy Data
Hypothesis Testing
Prediction
Software
Complexity
Vulnerabilities
Legalities
Social and Ethical Issues