By Gordon S. Linoff, Michael J. A. Berry
The top introductory e-book on information mining, absolutely up-to-date and revised!
When Berry and Linoff wrote the 1st variation of Data Mining Techniques within the overdue Nineties, information mining used to be simply beginning to circulate out of the lab and into the place of work and has due to the fact grown to turn into an essential software of recent company. This new edition—more than 50% new and revised— is an important replace from the former one, and exhibits you the way to harness the most recent facts mining tools and methods to unravel universal company difficulties. The duo of exceptional authors percentage helpful suggestion for bettering reaction charges to direct advertising campaigns, picking new consumer segments, and estimating credits hazard. additionally, they hide extra complex themes reminiscent of getting ready information for research and developing the required infrastructure for facts mining at your company.
- Features major updates because the earlier version and updates you on most sensible practices for utilizing info mining tools and methods for fixing universal company problems
- Covers a brand new info mining process in each bankruptcy besides transparent, concise factors on tips on how to practice every one method immediately
- Touches on center information mining strategies, together with selection bushes, neural networks, collaborative filtering, organization ideas, hyperlink research, survival research, and more
- Provides top practices for appearing information mining utilizing uncomplicated instruments akin to Excel
Data Mining ideas, 3rd Edition covers a brand new info mining method with each one successive bankruptcy after which demonstrates how one can follow that method for greater advertising and marketing, revenues, and customer service to get instant results.
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Additional info for Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management
Gordon and Michael are dedicated to sharing their knowledge, skills, and enthusiasm for the subject. When not mining data themselves, they enjoy teaching others through courses, lectures, articles, on-site classes, and of course, the book you are about to read. They can frequently be found speaking at conferences and teaching classes. com. Gordon lives in Manhattan. His most recent book before this one is Data Analysis Using SQL and Excel, which was published by Wiley in 2008. Michael lives in Cambridge, Massachusetts.
Chapter 18 is about finding the customer in the data and building customer signatures, the data structure used by many data mining algorithms. Chapter 19 covers derived variables, with hints and tips on defining variables that help models perform better. Chapter 20 focuses on reducing the number of variables, whether for techniques such as neural networks that prefer fewer variables or for data visualization purposes. One of the key techniques in this chapter, principal components, is new in this edition.
To bring a range of data mining techniques to bear on the problem. There was no shortage of data. For many years, BofA had been storing data on its millions of retail customers in a large relational database on a powerful parallel computer from Teradata. Data from 42 systems of record was cleansed, transformed, aligned, and then fed into the corporate data warehouse. With this system, BofA could see all the relationships each customer maintained with the bank. This historical database was truly worthy of the name — some records dated back to 1914!
Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management by Gordon S. Linoff, Michael J. A. Berry