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Data Analysis Using SQL and Excel

Data Analysis Using SQL and Excel - Second Edition

By : Gordon S. S. Linoff
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Data Analysis Using SQL and Excel

Data Analysis Using SQL and Excel

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)
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1
Foreword
17
EULA

Year-over-Year Comparisons

The previous year usually provides the best comparison for what is happening the following year. This section talks about such comparisons, with particular emphasis on one of the big challenges. This year’s data is usually not complete, so how can we make a valid comparison?

Comparisons by Day

The place to start is with day-by-day comparisons from one year to the next. Here is a method where much of the work is done in Excel:

  1. Query the database and aggregate by date.
  2. Load the data into Excel, with all the dates in one column.
  3. Pivot the data into 366 rows (for each day in the year) and a separate column for each year.

This is actually more work than necessary. An easier way is to use the MONTH(), DAY(), and YEAR() functions in SQL to create the resulting table directly, as in the following example using starts from Subscribers:

SELECT MONTH(StartDate) as mon, DAY(StartDate) as dom,
       SUM(CASE WHEN YEAR(StartDate) = 2004 THEN 1 ELSE 0 END) as n2004...
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Data Analysis Using SQL and Excel
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