Principles of Big Data

Preparing, Sharing, and Analyzing Complex Information

Nonfiction, Computers, Database Management, Data Processing, General Computing
Cover of the book Principles of Big Data by Jules J. Berman, Elsevier Science
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Jules J. Berman ISBN: 9780124047242
Publisher: Elsevier Science Publication: May 20, 2013
Imprint: Morgan Kaufmann Language: English
Author: Jules J. Berman
ISBN: 9780124047242
Publisher: Elsevier Science
Publication: May 20, 2013
Imprint: Morgan Kaufmann
Language: English

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
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Elsevier Science

Cover of the book Forensic Science by Jules J. Berman
Cover of the book Progress in Nucleic Acid Research and Molecular Biology by Jules J. Berman
Cover of the book Red Cell Development by Jules J. Berman
Cover of the book Immunology Guidebook by Jules J. Berman
Cover of the book Enzymes of Epigenetics Part B by Jules J. Berman
Cover of the book Diet and Exercise in Cystic Fibrosis by Jules J. Berman
Cover of the book Peering Carrier Ethernet Networks by Jules J. Berman
Cover of the book Flexible and Focused by Jules J. Berman
Cover of the book Advances in Computers by Jules J. Berman
Cover of the book Green Vegetable Oil Processing by Jules J. Berman
Cover of the book The Invisible Librarian by Jules J. Berman
Cover of the book Power Quality in Power Systems and Electrical Machines by Jules J. Berman
Cover of the book Annual Reports on NMR Spectroscopy by Jules J. Berman
Cover of the book Viral Ecology by Jules J. Berman
Cover of the book Foods, Nutrients and Food Ingredients with Authorised EU Health Claims by Jules J. Berman
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy