Data Analysis Using SQL and Excel
(Sprache: Englisch)
Mastering Data Analysis and Mining with SQL and Excel shows business managers and data analysts how to use the relatively simple tools of SQL and Excel to extract useful business information from relational databases. The book is organized around chapters...
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Produktinformationen zu „Data Analysis Using SQL and Excel “
Mastering Data Analysis and Mining with SQL and Excel shows business managers and data analysts how to use the relatively simple tools of SQL and Excel to extract useful business information from relational databases. The book is organized around chapters that become increasingly complex in the use of SQL, Excel, and data mining concepts.
Klappentext zu „Data Analysis Using SQL and Excel “
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 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
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.
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.
Inhaltsverzeichnis zu „Data Analysis Using SQL and Excel “
ForewordAcknowledgments
Introduction
Chapter 1 A Data Miner Looks at SQL
Chapter 2 What's In a Table? Getting Started with Data Exploration
Chapter 3 How Different Is Different
Chapter 4 Where Is It All Happening? Location, Location, Location
Chapter 5 It's a Matter of Time
Chapter 6 How Long Will Customers Last? Survival Analysis to Understand Customers and Their Value
Chapter 7 Factors Affecting Survival: The What and Why of Customer Tenure
Chapter 8 Customer Purchases and Other Repeated Events
Chapter 9 What's in a Shopping Cart? Market Basket Analysis and Association Rules
Chapter 10 Data Mining Models in SQL
Chapter 11 The Best-Fit Line: Linear Regression Models
Chapter 12 Building Customer Signatures for Further Analysis
Appendix Equivalent Constructs Among Databases
Index
Autoren-Porträt von Gordon S. Linoff
GORDON S. LINOFF is a cofounder of Data Miners, Inc., a consultancy specializing in data mining. He is the coauthor of the bestselling Data Mining Techniques, Second Edition, and Mastering Data Mining (both from Wiley). He has more than a decade of experience applying data mining techniques to business problems in marketing and customer relationship management.
Bibliographische Angaben
- Autor: Gordon S. Linoff
- 2007, 1. Auflage, 696 Seiten, Maße: 23,4 cm, Kartoniert (TB), Englisch
- Verlag: Wiley & Sons
- ISBN-10: 0470099518
- ISBN-13: 9780470099513
Sprache:
Englisch
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