Phranakorn Rajabhat University Library
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Principles and practice of big data / Jules J. Berman

By: Material type: TextTextPublication details: Academic Press, 2018 London :Description: XXVIII, 452 p. : ill. ; 24 cmISBN:
  • 9780128156094
Other title:
  • Principles and practice of big data: Preparing, sharing, and analyzing complex information
Subject(s): LOC classification:
  • QA 76.9.B45 B47P 2018
Contents:
1. Introduction page 1-14 -- 2. Providing structure to unstructured data page 15-52 --3. Identification, deidentification, and reidentification page 53-84 -- 4. Metadata, semantics, and triples page 85-96 -- 5.Classifications and ontologies page 97-136 -- 6. Introspection page 137-154 -- 7. Standards and data integration page 155-168 -- 8. Immutability and immortality page 169-184 -- 9. Assessing the adequacy of a big data resource page 185-206 -- 10. Measurement page 207-230
11. Indispensable tips for fast and simple big data analysis page 231-258 -- 12. Finding the clues in large collections of data page 259-276 -- 13. Using random numbers to knock your big data analytic problems down to size page 277-302 -- 14. Special considerations in big data analysis page 303-320 -- 15. Big data failures and how to avoid (some of) them page 321-350 -- 16. Data reanalysis: Much more important than analysis page 351-362 -- 17. Repurposing Big data page 363-372 -- 18. Data sharing and data security page 373-394 -- 19. Legalities page 395-418 -- 20. Societal issues page 419-444
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Holdings
Item type Current library Collection Shelving location Call number Status Barcode
General Book General Book SPU Library, Chonburi campus General Books (ENGLISH) Floor 3: General Shelves (FOREIGN LANGUAGE) QA 76.9.B45 B47P 2018 (Browse shelf(Opens below)) Available B009080
Total holds: 0

1. Introduction page 1-14 -- 2. Providing structure to unstructured data page 15-52 --3. Identification, deidentification, and reidentification page 53-84 -- 4. Metadata, semantics, and triples page 85-96 -- 5.Classifications and ontologies page 97-136 -- 6. Introspection page 137-154 -- 7. Standards and data integration page 155-168 -- 8. Immutability and immortality page 169-184 -- 9. Assessing the adequacy of a big data resource page 185-206 -- 10. Measurement page 207-230

11. Indispensable tips for fast and simple big data analysis page 231-258 -- 12. Finding the clues in large collections of data page 259-276 -- 13. Using random numbers to knock your big data analytic problems down to size page 277-302 -- 14. Special considerations in big data analysis page 303-320 -- 15. Big data failures and how to avoid (some of) them page 321-350 -- 16. Data reanalysis: Much more important than analysis page 351-362 -- 17. Repurposing Big data page 363-372 -- 18. Data sharing and data security page 373-394 -- 19. Legalities page 395-418 -- 20. Societal issues page 419-444

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