6119664
9780470099513
Leverage the power of SQL and Excel to perform business analysisThree key efforts are essential to effectively transform data into actionable information: retrieving data with SQL, presenting data with Excel, and understanding statistics as the foundation of data analysis. Data mining expert Gordon Linoff focuses on these topics and shows you how SQL and Excel can be used to extract business information from relational databases. He begins by taking a look at how data is central to the task of understanding customers, products, and markets, and he then goes on to show you how to use that data to define business dimensions, store transactions about customers, and summarize important data to produce results. Along the way, he shares stories based on his personal experience in the field, intended to enrich your understanding of why some things work-and others don't.Each chapter explains when and why to perform a particular type of business analysis in order to obtain useful results, how to design and perform the analysis using SQL and Excel, and what you can expect the results to look like. Throughout the book, critical features of Excel are highlighted, interesting uses of Excel graphics are explained, and dataflows and graphical representations of data processing are used to illustrate how SQL works.Data Analysis Using SQL and Excel shares hints, warnings, and technical asides about Excel, SQL, and data analysis/mining. The book also discusses:How entity-relationship diagrams describe the structure of dataWays to use SQL to generate SQL queriesDescriptive statistics, such as averages, p-values, and the chi-square testHow to incorporate geographic information into data analysisBasic ideas of hazard probabilities and survivalHow data structures summarize what a customer looks like at a specific point in timeSeveral variants of linear regressionThe companion Web site provides the data sets, Excel spreadsheets, and examples featured in the book.Linoff, Gordon S. is the author of 'Data Analysis Using SQL and Excel', published 2007 under ISBN 9780470099513 and ISBN 0470099518.
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