Data Analysis Using SQL and Excel / Edition 1

Data Analysis Using SQL and Excel / Edition 1

by Gordon S. Linoff
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Data Analysis Using SQL and Excel / Edition 1

Leverage the power of SQL and Excel to perform business analysis

Three 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 data
  • Ways to use SQL to generate SQL queries
  • Descriptive statistics, such as averages, p-values, and the chi-square test
  • How to incorporate geographic information into data analysis
  • Basic ideas of hazard probabilities and survival
  • How data structures summarize what a customer looks like at a specific point in time
  • Several variants of linear regression

The companion Web site provides the data sets, Excel spreadsheets, and examples featured in the book.

Product Details

ISBN-13: 9780470099513
Publisher: Wiley
Publication date: 10/01/2007
Edition description: Older Edition
Pages: 696
Product dimensions: 7.40(w) x 9.25(h) x 1.50(d)

Table of Contents

Foreword xxxiii

Introduction xxxvii

Chapter 1 A Data Miner Looks at SQL 1

Chapter 2 What’s in a Table? Getting Started with Data Exploration 49

Chapter 3 How Different Is Different? 97

Chapter 4 Where Is It All Happening? Location, Location, Location 145

Chapter 5 It’s a Matter of Time 197

Chapter 6 How Long Will Customers Last? Survival Analysis to Understand Customers and Their Value 255

Chapter 7 Factors Affecting Survival: The What and Why of Customer Tenure 315

Chapter 8 Customer Purchases and Other Repeated Events 367

Chapter 9 What’s in a Shopping Cart? Market Basket Analysis 421

Chapter 10 Association Rules and Beyond 465

Chapter 11 Data Mining Models in SQL 507

Chapter 12 The Best-Fit Line: Linear Regression Models 561

Chapter 13 Building Customer Signatures for Further Analysis 609

Chapter 14 Performance Is the Issue: Using SQL Effectively 655

Appendix Equivalent Constructs Among Databases 703

Index 731

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Data Analysis Using SQL and Excel 5 out of 5 based on 0 ratings. 2 reviews.
Anonymous More than 1 year ago
Guest More than 1 year ago
Utilizing data to drive results is critical to the success of any organization. Many know this to be true, but don¿t know how to go about it. 'Data Analysis Using SQL and Excel' by Gordon Linoff successfully shows the way using a holistic approach of ¿data ¿ analysis ¿ presentation¿. Its success is based on a number attributes including.... 1. Wide Audience: Different groups of people are addressed. Management and leadership will see what is possible with great examples 'e.g. Three Scenarios' on pg 333'. 'Doers' 'e.g. analysts' get a clear view of the big picture along with the ever so important how-to aspects 'which is often not included in other texts'. 2. Popular Tools: As the title states, this book utilizes Microsoft Excel and SQL. Not only are these tools often readily available, but many people are familiar with at least one of these, if not both. This familiarity enables the reader to focus more on learning useful approaches than the tools themselves. 3. Methods: A host of useful methods are covered from Survival Analysis to the more traditional like RFM. All, especially those related to statistics, are explained well ¿ simple but not so simple as to be inaccurate or incomplete. In my opinion, ¿Data Analysis Using SQL and Excel¿ is invaluable to those who want to get the most out of their organization¿s data.