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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Data is getting larger and extra advanced by way of the day, and so are the alternatives in dealing with that info. As a contemporary software developer you must comprehend the rising box of information administration, either RDBMS and NoSQL. Seven Databases in Seven Weeks takes you on a travel of a few of the most well liked open resource databases at the present time. within the culture of Bruce A. Tate's Seven Languages in Seven Weeks, this publication is going past your easy instructional to discover the basic thoughts on the center each one technology.
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notice the CAP theorem and its implications in your allotted information. comprehend the tradeoffs among consistency and availability, and should you can use them on your virtue. Use a number of databases in live performance to create a platform that's greater than the sum of its components, or locate one who meets your entire wishes at once.
Seven Databases in Seven Weeks will take you on a deep dive into all of the databases, their strengths and weaknesses, and the way to settle on those that suit your needs.
What You Need:
To get the main of of this booklet you'll need to persist with alongside, and that implies you'll want a *nix shell (Mac OSX or Linux hottest, home windows clients will want Cygwin), and Java 6 (or larger) and Ruby 1. eight. 7 (or greater). each one bankruptcy will record the downloads required for that database.
T-SQL is the elemental language for database programming in SQL Server 2005. All specialist SQL Server clients want to know it and, much more very important, needs to know the way to exploit it good. The language has grown significantly on account that SQL Server 2000 or even skilled T-SQL programmers have many new gains to grasp.
250+ Ready-to-Use, robust DMX Queries remodel info mining version details into actionable company intelligence utilizing the knowledge Mining Extensions (DMX) language. useful DMX Queries for Microsoft SQL Server research companies 2008 comprises greater than 250 downloadable DMX queries you should use to extract and visualize info.
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Extra info for Data Analysis Using SQL and Excel
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.