Principles of big data : preparing, sharing, and analyzing complex information / Jules J Berman.

By:

Berman, Jules J

Material type: Text

TextPublication details: Amsterdam : Elsevier, Morgan Kaufmann, c2013.Description: xxvi, 261 p. ; 25 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9780124045767

Subject(s):

DDC classification:

005.74 22 B.J.P

LOC classification:

QA76.9.D32 B47 2013

Online resources:

Abstract

Contents:

Summary: "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.

Average rating: 0.0 (0 votes)

Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Books	Main library A2	Computers & Information Technology ( Information systems )	005.74 B.J.P (Browse shelf(Opens below))	Available		00013309

Browsing Main library shelves, Shelving location: A2 Close shelf browser (Hides shelf browser)

Previous								Next
Previous	005.74 B Big data : (cover hadoop2, mapreduce, hive, yarn, pig, r and data visualization).	005.74 B.A.D Database security /	005.74 B.J.D Data warehouse : practical advice from the experts /	005.74 B.J.P Principles of big data : preparing, sharing, and analyzing complex information /	005.74 C.R.A Advanced Database Management System /	005.74 D The data warehouse lifecycle toolkit /	005.74 D The data warehouse lifecycle toolkit /	Next

computer bookfair2015

Includes bibliographical references and index (pages 247-255).

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.

"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.

There are no comments on this title.

to post a comment.