Big Data, Mining, and Analytics: Components of Strategic Decision Making
Kudyba, Stephan
- 出版商: Auerbach Publication
- 出版日期: 2019-10-23
- 售價: $2,740
- 貴賓價: 9.5 折 $2,603
- 語言: 英文
- 頁數: 325
- 裝訂: Quality Paper - also called trade paper
- ISBN: 0367378817
- ISBN-13: 9780367378813
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相關分類:
大數據 Big-data
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其他版本:
Big Data, Mining, and Analytics: Components of Strategic Decision Making (Hardcover)
相關主題
商品描述
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--Hadoop is just the beginning
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 to supply you with the well-rounded understanding required to leve
作者簡介
Stephan Kudyba has developed computerized models for trading financial markets in the investment banking industry and has provided Business Intelligence based solutions involving data mining applications for organizations across industry sectors. He has published numerous books and articles, has been interviewed by prominent magazines and speaks at corporate and academic events addressing data, information and knowledge management and organizational performance.
Dr. Kudyba is a professor in the school of management at New Jersey Institute of Technology where he teaches business courses addressing data, information and knowledge management, market research and internet marketing. He has held editorial positions for academic journals, is a member of a number of information management based societies, and maintains relations with organizations in a variety of industries addressing strategic initiatives.