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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

Starting to Investigate Dates

This section covers some basics when looking at date columns. The companion data sets have several date columns. Subscriptions contains the start date and stop date of subscriptions. Orders contains the order date, and the related OrderLines contains the billing date and shipping date for each line item in the order. Throughout this chapter, all these dates are used in examples. This section starts by looking at the date values themselves, and continues from there.

Verifying That Dates Have No Times

Sometimes, the result set for a query shows only the date components of datetime values, and not the time components. The date part is usually more interesting; and, leaving out the time reduces the width needed for output. Non-zero time values may not be visible, which can be misleading. For instance, two dates might look equal—say, as 2014-01-01. In a comparison, the two dates might not be equal because one is for noon and the other for midnight. Also...

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Data Analysis Using SQL and Excel
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