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Free ebooks
 Free database ebooks SQL Data Analysis Using SQL and Excel - Wiley Publishing
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 The first chapter, “A Data Miner Looks at SQL,” introduces SQL from the perspective of data analysis. This is the querying part of the SQL language, where data stored in databases is extracted using SQL queries.The second chapter, “What’s In a Table? Getting Started with Data Exploration,” introduces Excel for exploratory data analysis and presentation. Of many useful capabilities in Excel, perhaps the most useful are charts. Chapter 3, “How Different Is Different?”, explains some key concepts of descriptive statistics, such as averages, p-values, and the chi-square test. The purpose of this chapter is to show how to use such statistics on data residing in tables. Chapter 4, “Where Is It All Happening? Location, Location, Location,” explains geography and how to incorporate geographic information into data analysis. Geography starts with locations, described by latitude and longitude. Chapter 5, “It’s a Matter of Time,” discusses another key attribute of customer behavior, when things occur. This chapter describes how to access features of dates and times in databases, and then how to use this information to understand customers. Chapters 6 and 7, “How Long Will Customers Last? Survival Analysis to Understand Customers and Their Value” and “Factors Affecting Survival: The What and Why of Customer Tenure,” explain one of the most important analytic techniques for understanding customers over time. Chapter 8 covers everything about the purchase—when it occurs, where it occurs, how often —except for the particular items being purchased. Purchases contain a lot of information, even before we dive into the details of the items. Chapter 9 explains association rules, which are combinations of products purchased at the same time or in sequence. Building association rules in SQL is rather sophisticated, usually requiring intermediate tables. Chapter 10, “Data Mining Models in SQL,” introduces the idea of data mining modeling and the terminology associated with building such models. It also discusses some important types of models that are well-suited to business problems and the SQL environment. Chapter 11, “The Best Fit Line: Linear Regression Models,” covers a more traditional statistical technique, linear regression. Several variants of linear regression are introduced, including polynomial regression, weighted regression, multiple regression, and exponential regression. The final chapter, “Building Customer Signatures for Further Analysis,” introduces the customer signature. This is a data structure that summarizes what a customer looks like at a particular point in time. Download free ebooks on SQL:Data Analysis Using SQL and Excel - Wiley Publishing
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