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Chapter 1 A Data Miner Looks at SQL.
Chapter 2 What’s In a Table? Getting Started with Data Exploration.
Chapter 3 How Different Is Different?
Chapter 4 Where Is It All Happening? Location, Location, Location.
Chapter 5 It’s a Matter of Time.
Chapter 6 How Long Will Customers Last? Survival Analysis to Understand Customers and Their Value.
Chapter 7 Factors Affecting Survival: The What and Why of Customer Tenure.
Chapter 8 Customer Purchases and Other Repeated Events.
Chapter 9 What’s in a Shopping Cart? Market Basket Analysis and Association Rules.
Chapter 10 Data Mining Models in SQL.
Chapter 11 The Best-Fit Line: Linear Regression Models.
Chapter 12 Building Customer Signatures for Further Analysis.
Appendix Equivalent Constructs Among Databases.
Posted January 31, 2008
Utilizing data to drive results is critical to the success of any organization. Many know this to be true, but don¿t know how to go about it. 'Data Analysis Using SQL and Excel' by Gordon Linoff successfully shows the way using a holistic approach of ¿data ¿ analysis ¿ presentation¿. Its success is based on a number attributes including.... 1. Wide Audience: Different groups of people are addressed. Management and leadership will see what is possible with great examples 'e.g. Three Scenarios' on pg 333'. 'Doers' 'e.g. analysts' get a clear view of the big picture along with the ever so important how-to aspects 'which is often not included in other texts'. 2. Popular Tools: As the title states, this book utilizes Microsoft Excel and SQL. Not only are these tools often readily available, but many people are familiar with at least one of these, if not both. This familiarity enables the reader to focus more on learning useful approaches than the tools themselves. 3. Methods: A host of useful methods are covered from Survival Analysis to the more traditional like RFM. All, especially those related to statistics, are explained well ¿ simple but not so simple as to be inaccurate or incomplete. In my opinion, ¿Data Analysis Using SQL and Excel¿ is invaluable to those who want to get the most out of their organization¿s data.
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Posted July 12, 2010
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