Waubonsee Community College

Data analysis using SQL and Excel, Gordon S. Linoff

eng

illustrations

index present

non fiction

Data analysis using SQL and Excel

dictionaries

189105261

Gordon S. Linoff

"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." "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."--Jacket

Cover -- About the Author -- Credits -- Contents -- Foreword -- Acknowledgments -- Introduction -- Overview of the Book and Technology -- How This Book Is Organized -- Who Should Read this Book -- Tools You Will Need -- What's on the Web Site -- Summary -- Chapter 1: A Data Miner Looks at SQL -- Picturing the Structure of the Data -- Picturing Data Analysis Using Dataflows -- SQL Queries -- Subqueries Are Our Friend -- Lessons Learned -- Chapter 2: What's In a Table? Getting Started with Data Exploration -- What Is Data Exploration? -- Excel for Charting -- What Values Are in the Columns? -- More Values to Explore -- Min, Max, and Mode -- Exploring String Values -- Exploring Values in Two Columns -- From Summarizing One Column to Summarizing All Columns -- Lessons Learned -- Chapter 3: How Different Is Different? -- Basic Statistical Concepts -- How Different Are the Averages? -- Counting Possibilities -- Ratios, and Their Statistics -- Chi-Square -- Lessons Learned -- Chapter 4: Where Is It All Happening? Location, Location, Location -- Latitude and Longitude -- Census Demographics -- Geographic Hierarchies -- Mapping in Excel -- Lessons Learned -- Chapter 5: It's a Matter of Time -- Dates and Times in Databases -- Starting to Investigate Dates -- How Long between Two Dates? -- Year-over-Year Comparisons -- Counting Active Customers by Day -- Simple Chart Animation in Excel -- Lessons Learned -- Chapter 6: How Long Will Customers Last? Survival Analysis to Understand Customers and Their Value -- Background on Survival Analysis -- The Hazard Calculation -- Survival and Retention -- Comparing Different Groups of Customers -- Comparing Survival over Time -- Important Measures Derived from Survival -- Using Survival for Customer Value Calculations -- Lessons Learned -- Chapter 7: Factors Affecting Survival: The What and Why of Customer Tenure -- What Factors Are Important and When -- Left Truncation -- Time Windowing -- Competing Risks -- Before and After -- Lessons Learned -- Chapter 8: Customer Purchases and Other Repeated Events -- Identifying Customers -- RFM Analysis -- Which Households Are Increasing Purchase Amounts Over Time? -- Time to Next Event -- Lessons Learned -- Chapter 9: What's in a Shopping Cart? Market Basket Analysis and Association Rules -- Exploratory Market Basket Analysis -- Combinations (Item Sets) -- The Simplest Association Rules -- One-Way Association Rules -- Two-Way Associations -- Extending Association Rules -- Lessons Learned -- Chapter 10: Data Mining Models in SQL -- Introduction to Directed Data Mining -- Look-Alike Models -- Lookup Model for Most Popular Product -- Lookup Model for Order Size -- Lookup Model for Probability of Response -- Naïve Bayesian Models (Evidence Models) -- Lessons Learned -- Chapter 11: The Best-Fit Line: Linear Regression Models -- The Best-Fit Line -- Measuring Goodness of Fit Using R2 -- Direct Calculation of Best-Fit Line Coefficients -- Weighted Linear Regressio