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

Picturing Data Analysis Using Dataflows

Tables store data, but tables do not actually do anything. Tables are nouns; queries are verbs. This book mates SQL and Excel for data manipulation, transformation, and presentation. The differences between these tools are exacerbated because they often support the same operations, although in very different ways. For instance, SQL uses the GROUP BY clause to summarize data in groups. An Excel user, on the other hand, might use pivot tables, use the subtotal wizard, or manually do calculations using functions such as SUMIF(); however, nothing in Excel is called “group by.”

Because this book intends to combine the two technologies, it is useful to have a common way of expressing data manipulations and data transformations, a common language independent of the tools being used. Dataflows provide this common language by showing the transformation operations fitting together like an architecture blueprint for data processing, a blueprint...