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

Introduction to Directed Data Mining

Directed data mining is the most common type of data mining. “Directed” means that the historical data used for modeling contains examples of the target values, so the data mining techniques have examples to learn from. Directed data mining also makes the assumption that the patterns in historical data are applicable in the future.

Another type of data mining is undirected data mining, which uses sophisticated techniques to find patterns in the data without the guidance of a target. Without a target, the algorithm cannot determine if the results are good or bad; as a consequence, undirected data mining requires additional human judgment to assess the results. Association rules are one example of undirected data mining. Other undirected techniques are typically more specialized, so this chapter and the next two focus on directed techniques.