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Data analysis using SQL and Excel /
"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 t...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Indianapolis, Ind. :
Wiley Pub.,
©2008.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- 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.