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Data Analysis Using SQL and Excel

Data Analysis Using SQL and Excel - Second Edition

By : Gordon S. S. Linoff
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Data Analysis Using SQL and Excel

Data Analysis Using SQL and Excel

By: Gordon S. S. Linoff

Overview of this book

Data Analysis Using SQL and Excel, 2nd Edition shows you how to leverage the two most popular tools for data query and analysis—SQL and Excel—to perform sophisticated data analysis without the need for complex and expensive data mining tools. Written by a leading expert on business data mining, this book shows you how to extract useful business information from relational databases. You'll learn the fundamental techniques before moving into the "where" and "why" of each analysis, and then learn how to design and perform these analyses using SQL and Excel. Examples include SQL and Excel code, and the appendix shows how non-standard constructs are implemented in other major databases, including Oracle and IBM DB2/UDB. The companion website includes datasets and Excel spreadsheets, and the book provides hints, warnings, and technical asides to help you every step of the way. Data Analysis Using SQL and Excel, 2nd Edition shows you how to perform a wide range of sophisticated analyses using these simple tools, sparing you the significant expense of proprietary data mining tools like SAS.
Table of Contents (18 chapters)
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1
Foreword
17
EULA

Which Factors Are Important and When

Survival analysis can be used to compare different groups of customers by creating a separate curve for each group. This process, called stratification, qualitatively shows the effect of market, or rate plan, or channel, or a combination of them, on survival.

This section shows how to quantify the effects at different tenures. For numeric variables, the comparison uses averages of the variable at different tenures for customers who stop and do not stop. For categorical variables, the comparison uses hazards ratios at different tenures. The key idea is that the effect of such variables may be stronger during some parts of the customer tenure and weaker during others. Being able to see the effects at different tenures sheds light on the effect of the variables on customer relationships.

Explanation of the Approach

Figure 7-1What differentiates the customer(s) who stop from the customer(s) who remain active?

Eight horizontal lines for Customer 1-8 on Tenure axis with white, black end points. Lines for Customer 1-3, 6-8 have white points on vertical line in-between start, end points.

Figure 7.1: At any given tenure, what differentiates...

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Data Analysis Using SQL and Excel
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