Big data, mining, and analytics : components of strategic decision making
著者
書誌事項
Big data, mining, and analytics : components of strategic decision making
（An Auerbach book）
CRC Press, c2014
- : hardback
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
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 Analytics
Introduces text mining and the transforming of unstructured data into useful information
Examines real time wireless medical data acquisition for today's healthcare and data mining challenges
Presents the contributions of big data experts from academia and industry, including SAS
Highlights the most exciting emerging technologies for big data
Filled 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.
目次
Introduction to the Big Data Era. Information Creation through Analytics. Big Data Analytics-Architectures, Implementation. Methodology, and Tools. Data Mining Methods and the Rise of Big Data. Data Management and Model Creation Process of Structured Data for Mining and Analytics. The Internet: A Source of New Data for Mining in Marketing. Mining and Analytics in E-Commerce. Streaming Data in the Age of Big Data. Using CEP for Real-Time Data Mining. Transforming Unstructured Data into Useful Information. Mining Big Textual Data. The New Medical Frontier: Real-Time Wireless Medical Data Acquisition for 21st-Century Healthcare and Data Mining Challenges.
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