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

CHAPTER 1
A Data Miner Looks at SQL

Data is being collected everywhere. Every transaction, every web page visit, every payment—and much more—is filling databases, relational and otherwise, with raw data. Computing power and storage have grown to be cost effective, a trend where today’s smart phones are more powerful than supercomputers of yesteryear. Databases are no longer merely platforms for storing data; they are powerful engines for transforming data into useful information about customers and products and business practices.

The focus on data mining has historically been on complex algorithms developed by statisticians and machine-learning specialists. Once upon a time, data mining required downloading source code from a research lab or university, compiling the code to get it to run, and sometimes even debugging it. By the time the data and software were ready, the business problem had lost urgency.

This book takes a different approach because it starts...