Commercial Data Mining
Processing, Analysis and Modeling for Predictive Analytics Projects
Published on 8. April 2014
Book
Paperback/Softback
304 pages
978-0-12-416602-8 (ISBN)
Description
Whether you are brand new to data mining or working on your tenth predictive analytics project, Commercial Data Mining will be there for you as an accessible reference outlining the entire process and related themes. In this book, you'll learn that your organization does not need a huge volume of data or a Fortune 500 budget to generate business using existing information assets. Expert author David Nettleton guides you through the process from beginning to end and covers everything from business objectives to data sources, and selection to analysis and predictive modeling.
Commercial Data Mining includes case studies and practical examples from Nettleton's more than 20 years of commercial experience. Real-world cases covering customer loyalty, cross-selling, and audience prediction in industries including insurance, banking, and media illustrate the concepts and techniques explained throughout the book.
Commercial Data Mining includes case studies and practical examples from Nettleton's more than 20 years of commercial experience. Real-world cases covering customer loyalty, cross-selling, and audience prediction in industries including insurance, banking, and media illustrate the concepts and techniques explained throughout the book.
Reviews / Votes
"...a mandatory volume for anyone who runs data mining projects, since all the steps and most important details that should not be forgotten are described here...I strongly recommend this book for anyone even slightly involved with data mining projects." --IEEE Communications Magazine, Commercial Data Mining"I strongly disagree with Bellin's statement that the book will not help practitioners, and one can only conclude that the reviewer is not familiar with what data mining practitioners need." -Computing Reviews, Oct 13, 2014
More details
Series
Language
English
Place of publication
San Francisco
United States
Publishing group
Elsevier Science & Technology
Target group
Professional and scholarly
Data mining professionals in business & IT.
Product notice
Paperback (trade)
Unsewn / adhesive bound
Illustrations
Illustrated
Dimensions
Height: 227 mm
Width: 154 mm
Thickness: 20 mm
Weight
493 gr
ISBN-13
978-0-12-416602-8 (9780124166028)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
David Nettleton
Commercial Data Mining
Processing, Analysis and Modeling for Predictive Analytics Projects
E-Book
01/2014
Morgan Kaufmann
€38.95
Available for download
Person
David F. Nettleton has more than 25 years of experience in IT system development, specializing in databases and data analysis. He has a Bachelor of Science degree in Computer Science, Master of Science degree in Computer Software and Systems Design and a Ph.D. in Artificial Intelligence. He has worked for IBM as a Business Intelligence Consultant, among other companies. In 1995 he founded his own consultancy dedicated to commercial data analysis projects, working in the Banking, Insurance, Media, Industry and Health Sectors. He has published over 40 articles and papers in journals, national and international congresses and magazines, and has given many presentations in conferences and workshops. He is currently a contract researcher at the Universitat Pompeu Fabra, Barcelona, Spain and at the IIIA-CSIC, Spain, specializing in data mining applied to online social networks and data privacy. Dr. Nettleton was born in England and lives in Barcelona, Spain since 1988.
Content
1. Introduction2. Business Objectives3. Data Quality4. Data Representation5. Possible Sources of Data and Information6. Selection of Variables and Factors7. Data Sampling8. Data Analysis9. Modeling10. The Data Mart - Structured Data Warehouse11. Querying, Report Generation and Executive Information Systems12. Analytical CRM - Customer Relationship Analysis13. Website Analysis and Internet Search14. Online Social Network Analysis15. Web Search Trend Analysis16. Creating your own Environment for Commercial Data Analysis17. SummaryAppendices, Case Studies