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Your guide to quickly turn data into results.

Transform your skills, data, and business—and create your own BI solutions using software you already know and love: Microsoft Excel. Two business intelligence (BI) experts take you inside PowerPivot functionality for Excel 2013, with a focus on real world scenarios, problem-solving, and data modeling. You'll learn how to quickly turn mass quantities of data into meaningful information and on-the-job results—no programming required!

• Understand the differences between PowerPivot for Self Service BI and SQL Server Analysis Services for Corporate BI
• Extend your existing data-analysis skills to create your own BI solutions
• Quickly manipulate large data sets, often in millions of rows
• Perform simple-to-sophisticated calculations and what-if analysis
• Create complex reporting systems with data modeling and Data Analysis Expressions
• Share your results effortlessly across your organization using Microsoft SharePoint

Authors’ note on using Microsoft Excel 2016: This book’s content was written against Excel 2013, but it is useful and valid for users of Excel 2016 too. Excel 2016 introduces several new DAX functions and an improved editor for DAX without changing any existing behavior. In other words, all of the concepts and examples explained in this book continue to work with Excel 2016.

Microsoft Excel 2013 Building Data Models with PowerPivot

• Introduction
• Chapter 1: Introduction to PowerPivot
• Chapter 2: Using the unique features of PowerPivot
• Chapter 3: Introducing DAX
• Chapter 4: Understanding data models
• Chapter 5: Publishing to SharePoint
• Chapter 6: Loading data
• Chapter 7: Understanding evaluation contexts
• Chapter 8: Understanding CALCULATE
• Chapter 9: Using hierarchies
• Chapter 10: Using Power View
• Chapter 11: Shaping the reports
• Chapter 12: Performing date calculations in DAX
• Chapter 13: Using advanced DAX
• Chapter 14: Using DAX as a query language
• Chapter 15: Automating operations using VBA
• Chapter 16: Comparing Excel and SQL Server Analysis Services
• About the Authors