logo
Supporting your high street Find out how »
Basket Image

Basket

Big Data, Mining, and Analytics : Components of Strategic Decision Making, Hardback Book

Big Data, Mining, and Analytics : Components of Strategic Decision Making Hardback

Description

There is an ongoing data explosion transpiring that will make previous creations, collections, and storage of data look trivial.

Big Data, Mining, and Analytics: Components of Strategic Decision Making ties together big data, data mining, and analytics to explain how readers can leverage them to extract valuable insights from their data.

Facilitating a clear understanding of big data, it supplies authoritative insights from expert contributors into leveraging data resources, including big data, to improve decision making. Illustrating basic approaches of business intelligence to the more complex methods of data and text mining, the book guides readers through the process of extracting valuable knowledge from the varieties of data currently being generated in the brick and mortar and internet environments.

It considers the broad spectrum of analytics approaches for decision making, including dashboards, OLAP cubes, data mining, and text mining. Includes a foreword by Thomas H. Davenport, Distinguished Professor, Babson College; Fellow, MIT Center for Digital Business; and Co-Founder, International Institute for AnalyticsIntroduces text mining and the transforming of unstructured data into useful informationExamines real time wireless medical data acquisition for today's healthcare and data mining challengesPresents the contributions of big data experts from academia and industry, including SASHighlights the most exciting emerging technologies for big dataFilled with examples that illustrate the value of analytics throughout, the book outlines a conceptual framework for data modeling that can help you immediately improve your own analytics and decision-making processes.

It also provides in-depth coverage of analyzing unstructured data with text mining methods.

Information

  • Format: Hardback
  • Pages: 325 pages, 4 page color insert follows page 48
  • Publisher: Taylor & Francis Ltd
  • Publication Date:
  • Category: Data mining
  • ISBN: 9781466568709

Other Formats