Book Image

Data Analysis Using SQL and Excel - Second Edition

By : Gordon S. S. Linoff
Book Image

Data Analysis Using SQL and Excel - Second Edition

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)
Free Chapter
1
Foreword
17
EULA

Subqueries and Common Table Expressions Are Our Friends

Subqueries are exactly what their name implies, queries within queries. They make it possible to do complex data manipulation within a single SQL statement, exactly the types of manipulation needed for data analysis and data mining.

In one sense, subqueries are not needed. All the manipulations could be accomplished by creating intermediate tables and combining them. The resulting SQL would be a series of CREATE TABLE statements and INSERT statements (or possibly CREATE VIEW or SELECT INTO), with simpler queries. Although such an approach is sometimes useful, especially when the intermediate tables are used multiple times, it suffers from several problems.

First, instead of thinking about solving a particular problem, you end up thinking about the data processing, the naming of intermediate tables, determining the types of columns, remembering to remove tables when they are no longer needed, deciding whether to build indexes, and...