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

What Is Data Exploration?

Data is stored in databases as bits and bytes, spread through tables and columns, in memory and on disk. Data lands there through various business processes. Operational databases capture the data as it is collected from customers—as they make airplane reservations, or complete telephone calls, or click on the web, or as their bills are generated. The databases used for data analysis are usually decision support databases and data warehouses where the data has been restructured and cleansed to conform to some view of the business.

Data exploration is the process of characterizing the data actually present in a database and understanding the relationships between various columns and entities. Data exploration is a hands-on effort. Metadata, documentation that explains what should be there, provides one description. Data exploration is about understanding what actually is there, and, if possible, understanding how and why it got there. Data exploration is...