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Big Data, Mining, and Analytics: Components of Strategic Decisio...
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Book 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.
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ISBN: 978-1-4665-6870-9
9 781466 568709
90000
Information Technology / Database
Just as early analytical competitors in the “small data” era moved out ahead of their
competitors and built a sizable competitive edge, the time is now for rms to seize the big
data opportunity. ... an excellent review of the opportunities involved in this revolution ...
The road to the Big Data Emerald City is paved with many potholes. Reading this book
can help you avoid many of them, and avoid surprise when your trip is still a bit bumpy.
—From the Foreword by Thomas H. Davenport, Distinguished Professor,
Babson College; Fellow, MIT Center for Digital Business; and Co-Founder,
International Institute for Analytics
There is an ongoing data explosion transpiring that will make previous creations, collec-
tions, 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
• 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 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 leverage your information assets into improved
strategic decision making.
6000 Broken Sound Parkway, NW
Suite 300, Boca Raton, FL 33487
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New York, NY 10017
2 Park Square, Milton Park
Abingdon, Oxon OX14 4RN, UK
an informa business
www.crcpress.com
K16400
www.auerbach-publications.com
Big Data, Mining, and Analytics
Components
of Strategic
Decision
Making
Stephan Kudyba
Foreword by Thomas H. Davenport
Big Data,
Mining, and
Analytics
Kudyba
K16400 cvr mech.indd 1 2/7/14 3:09 PM
Big Data,
Mining, and
Analytics
Components of
Strategic Decision Making
Big Data,
Mining, and
Analytics
Components of
Strategic Decision Making
Stephan Kudyba
Foreword by
Thomas H. Davenport
CRC Press
Taylor & Francis Group
6000 Broken Sound Parkway NW, Suite 300
Boca Raton, FL 33487-2742
© 2014 by Taylor & Francis Group, LLC
CRC Press is an imprint of Taylor & Francis Group, an Informa business
No claim to original U.S. Government works
Version Date: 20140203
International Standard Book Number-13: 978-1-4665-6871-6 (eBook - PDF)
This book contains information obtained from authentic and highly regarded sources. Reasonable efforts
have been made to publish reliable data and information, but the author and publisher cannot assume
responsibility for the validity of all materials or the consequences of their use. The authors and publishers
have attempted to trace the copyright holders of all material reproduced in this publication and apologize to
copyright holders if permission to publish in this form has not been obtained. If any copyright material has
not been acknowledged please write and let us know so we may rectify in any future reprint.
Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmit-
ted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented,
including photocopying, microfilming, and recording, or in any information storage or retrieval system,
without written permission from the publishers.
For permission to photocopy or use material electronically from this work, please access www.copyright.
com (http://www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood
Drive, Danvers, MA 01923, 978-750-8400. CCC is a not-for-profit organization that provides licenses and
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Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used
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and the CRC Press Web site at
http://www.crcpress.com
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资源评论
- smilelee04092014-12-06这本书非常全面。值得阅读。
- jjdmn2015-07-31本书内容浅显易懂,值得推荐!
- babatada2016-04-25简单,但只介绍了大数据的基本应用,具体技术介绍较少。
jerrylees2006
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