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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 Customers Have Particular Products?

This section moves from any product to particular products. It is also going to introduce aggregate string concatenation, an operation that is unfortunately not part of the SQL standard. So every database has a different method—with SQL Server’s being the most arcane. Let’s start with the most popular products and the customers who purchase them.

Which Customers Have the Most Popular Products?

It is easy to get the list of the most popular products by using an aggregation query. Let’s ask a slight variation on this question: How many customers purchase the ten most popular products? As a further refinement, let’s ask how many customers purchase one, two, three, and so on of these products.

The following query uses a subquery to identify the most popular products. This subquery is used in the WHERE clause in the subquery:

SELECT cnt, COUNT(*) as households
FROM (SELECT c.HouseholdId, COUNT(DISTINCT ol.ProductId...
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Data Analysis Using SQL and Excel
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