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Big Data, Mining, and Analytics

Components of Strategic Decision Making
Book Hero Magic crafted this summary to help describe this book. While it's new and still learning, it may not be perfect - your feedback is welcome! Summary
Big Data, Mining, and Analytics: Components of Strategic Decision Making explores the expanding world of big data, data mining, and analytics to help readers extract valuable insights from vast datasets. The book demystifies complex concepts with clear explanations, covering business intelligence fundamentals, advanced data and text mining methods, and a wide range of analytics tools like dashboards and OLAP cubes. It includes expert contributions on leveraging big data for enhanced decision making, examines real-time data acquisition challenges in healthcare, and highlights emerging technologies shaping the future of data analytics.
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Format: Hardback
$16000
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Book Hero Magic created this recommendation. While it's new and still learning, it may not be perfect - your feedback is welcome! IS THIS YOUR NEXT READ?

This book is ideal for professionals and students in computing and technology fields who seek to deepen their understanding of big data analytics and its strategic applications in decision making. It benefits data scientists, business analysts, and healthcare IT specialists looking for practical examples and expert insights to advance their analytical skills.

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Book Hero Magic formatted this description to make it easier to read. While it's new and still learning, it may not be perfect - your feedback is welcome! 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 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 modelling that can help you immediately improve your own analytics and decision-making processes. It also provides in-depth coverage of analysing unstructured data with text mining methods.

Book Details

INFORMATION

ISBN: 9781466568709

Publisher: Taylor & Francis Ltd

Format: Hardback

Date Published: 12 March 2014

Country: United Kingdom

Imprint: Auerbach

Illustration: 9 Tables, black and white; 89 Illustrations, black and white

Audience: Tertiary education, Professional and scholarly

DIMENSIONS

Width: 156.0mm

Height: 234.0mm

Weight: 596g

Pages: 326

About the Author

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.

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