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Business intelligence and data mining / Anil K. Maheshwari.

By: Material type: TextTextSeries: Big data and business analytics collectionPublisher: New York, New York (222 East 46th Street, New York, NY 10017) : Business Expert Press, 2015Edition: First editionDescription: 1 online resource (xiv, 162 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781631571213
Subject(s): Genre/Form: Additional physical formats: Print version:: No titleDDC classification:
  • 658.4038 23
LOC classification:
  • HF54.5 .M243 2015
Online resources:
Contents:
1. Wholeness of business intelligence and data mining -- 2. Business intelligence concepts and applications -- 3. Data warehousing -- 4. Data mining -- 5. Decision trees -- 6. Regression -- 7. Artificial neural networks -- 8. Cluster analysis -- 9. Association rule mining -- 10. Text mining -- 11. Web mining -- 12. Big data -- 13. Data modeling primer -- Additional resources -- Index.
Abstract: Business is the act of doing something productive to serve someone's needs, and thus earn a living, and make the world a better place. Business activities are recorded on paper or using electronic media, and then these records become data. There is more data from customers' responses and on the industry as a whole. All this data can be analyzed and mined using special tools and techniques to generate patterns and intelligence, which reflect how the business is functioning. These ideas can then be fed back into the business so that it can evolve to become more effective and efficient in serving customer needs. And the cycle continues on. Business intelligence includes tools and techniques for data gathering, analysis, and visualization for helping with executive decision making in any industry. Data mining includes statistical and machine-learning techniques to build decision-making models from raw data. Data mining techniques covered in this book include decision trees, regression, artificial neural networks, cluster analysis, and many more. Text mining, web mining, and big data are also covered in an easy way. A primer on data modeling is included for those uninitiated in this topic.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Ebrary Online Books Ebrary Online Books Colombo Available CBEBK20001801
Ebrary Online Books Ebrary Online Books Jaffna Available JFEBK20001801
Ebrary Online Books Ebrary Online Books Kandy Available KDEBK20001801
Total holds: 0

Enhanced descriptions from Syndetics:

"This book is a splendid and valuable addition to this subject. The whole book is well written and I have no hesitation to recommend that this can be adapted as a textbook for graduate courses in Business Intelligence and Data Mining." Dr. Edi Shivaji, Des Moines, Iowa "As a complete novice to this area just starting out on a MBA course I found the book incredibly useful and very easy to follow and understand. The concepts are clearly explained and make it an easy task to gain an understanding of the subject matter." -- Mr. Craig Domoney, South Africa. Business Intelligence and Data Mining is a conversational and informative book in the exploding area of Business Analytics. Using this book, one can easily gain the intuition about the area, along with a solid toolset of major data mining techniques and platforms. This book can thus be gainfully used as a textbook for a college course. It is also short and accessible enough for a busy executive to become a quasi-expert in this area in a couple of hours. Every chapter begins with a case-let from the real world, and ends with a case study that runs across the chapters.

Includes bibliographical references (pages 157-158) and index.

1. Wholeness of business intelligence and data mining -- 2. Business intelligence concepts and applications -- 3. Data warehousing -- 4. Data mining -- 5. Decision trees -- 6. Regression -- 7. Artificial neural networks -- 8. Cluster analysis -- 9. Association rule mining -- 10. Text mining -- 11. Web mining -- 12. Big data -- 13. Data modeling primer -- Additional resources -- Index.

Access restricted to authorized users and institutions.

Business is the act of doing something productive to serve someone's needs, and thus earn a living, and make the world a better place. Business activities are recorded on paper or using electronic media, and then these records become data. There is more data from customers' responses and on the industry as a whole. All this data can be analyzed and mined using special tools and techniques to generate patterns and intelligence, which reflect how the business is functioning. These ideas can then be fed back into the business so that it can evolve to become more effective and efficient in serving customer needs. And the cycle continues on. Business intelligence includes tools and techniques for data gathering, analysis, and visualization for helping with executive decision making in any industry. Data mining includes statistical and machine-learning techniques to build decision-making models from raw data. Data mining techniques covered in this book include decision trees, regression, artificial neural networks, cluster analysis, and many more. Text mining, web mining, and big data are also covered in an easy way. A primer on data modeling is included for those uninitiated in this topic.

Title from PDF title page (viewed on January 26, 2015).

Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.

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