TY  - BOOK
AU  - Berman,Jules J.
TI  - Principles of big data: preparing, sharing, and analyzing complex information 
SN  - 9780124047242
AV  - QA76.9.D32 B47 2013eb
U1  - 005.74 23
PY  - 2013///]
CY  - Amsterdam
PB  - Elsevier, Morgan Kaufmann
KW  - Big data
KW  - Database management
KW  - Données volumineuses
KW  - Bases de données
KW  - Gestion
KW  - COMPUTERS
KW  - Database Management
KW  - General
KW  - bisacsh
KW  - Desktop Applications
KW  - Databases
KW  - System Administration
KW  - Storage & Retrieval
KW  - fast
N1  - Includes bibliographical references and index; 1. Providing structure to unstructured data -- 2. Identification, deidentification, and reidentification -- 3. Ontologies and semantics -- 4. Introspection -- 5. Data integration and software interoperability -- 6. Immutability and immortality -- 7. Measurement -- 8. Simple but powerful big data techniques -- 9. Analysis -- 10. Special considerations in big data analysis -- 11. Stepwise approach to big data analysis -- 12. Failure -- 13. Legalities -- 14. Societal issues -- 15. The future
N2  - "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. . 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"--Provided by publisher
UR  - https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=486639
ER  -