Excel Business Intelligence: Power Pivot and DAX

Learn how to use Power Pivot and the DAX language to explore and analyze relational data models in Excel.

Data Analysis Expressions (DAX) allow Microsoft Excel users to create powerful calculated fields in Power Pivot. In this course—the third and final installment of the Excel Business Intelligence series—experienced Excel trainer Chris Dutton spells out how to use the DAX language and Power Pivot to explore and analyze relational data models. Chris picks up where he left off in the previous installment of the series, demonstrating how to add calculated columns and measures to data models in Excel. He highlights the differences between calculated columns and DAX measures, covers common DAX formulas and functions, and discusses best practices for working with DAX and Power Pivot.

Introduction

• Welcome

1. Getting Started

• Important: Versions and compatibility
• Set expectations

2. Power Pivot and DAX 101

• Introduction to Power Pivot and DAX
• Create a Power Pivot table
• Power Pivots versus normal pivots
• Introduction to Data Analysis Expressions (DAX)
• Calculated columns
• DAX measures
• Create implicit measures
• Create explicit measures (AutoSum)
• Create explicit measures (Power Pivot)
• Understand filter context
• Step-by-step measure calculation
• Recap: Calculated columns versus measures
• Power Pivot best practices

3. Common DAX Functions

• Introduction to DAX functions
• DAX formula syntax and operators
• Common DAX function categories
• Basic math and stats functions
• COUNT, COUNTA, DISTINCTCOUNT, and COUNTROWS
• Logical Functions (IF, AND, and OR)
• Switch and Switch (TRUE)
• Text functions
• The CALCULATE function
• Add filter context with FILTER: Part 1
• Add filter context with FILTER: Part 2
• Remove filter context with ALL
• Join data with RELATED
• Iterator ("X") functions: SUMX
• Iterator ("X") functions: RANKX
• Basic date and time functions
• Time intelligence formulas
• Speed and performance considerations
• DAX best practices

Conclusion

• Final section
• Data visualization options
• Conclusion