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Data Analysis Using SQL and Excel by Gordon S. Linoff

By Gordon S. Linoff

Worthwhile company research calls for you to successfully rework facts into actionable details. This e-book is helping you employ SQL and Excel to extract company details from relational databases and use that information to outline company dimensions, shop transactions approximately shoppers, produce effects, and extra. every one bankruptcy explains whilst and why to accomplish a selected kind of enterprise research on the way to receive priceless effects, find out how to layout and practice the research utilizing SQL and Excel, and what the consequences should still seem like.

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Extra info for Data Analysis Using SQL and Excel

Sample text

Of many useful capabilities in Excel, perhaps the most useful are charts. As the ancient Chinese saying goes, “a picture paints a thousand words,” and Excel makes it possible to paint pictures using data. Such charts are not only useful aesthetically, but more practically for Word documents, PowerPoint, email, the Web, and so on. Charts are not a means unto themselves. This chapter starts down the road of exploratory data analysis, using charts to convey interesting summaries of data. In addition, this chapter discusses summarizing columns in a table, as well as the interesting idea of using SQL to generate SQL queries.

As the ancient Chinese saying goes, “a picture paints a thousand words,” and Excel makes it possible to paint pictures using data. Such charts are not only useful aesthetically, but more practically for Word documents, PowerPoint, email, the Web, and so on. Charts are not a means unto themselves. This chapter starts down the road of exploratory data analysis, using charts to convey interesting summaries of data. In addition, this chapter discusses summarizing columns in a table, as well as the interesting idea of using SQL to generate SQL queries.

Chapter 2 shows techniques to determine whether this condition holds for any given column. Numeric values are values that support arithmetic and other mathematical operations. In SQL, these can be stored in different ways, such as floatingpoint numbers, integers, decimals, and long integers. The details of how these formats differ is much less important than what can be done with numeric data types. Within the category of numeric types, one big difference is between integers, which have no fractional part, and real numbers, which do.

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