This course is No. 7 in the Microsoft® Power BI® series of webinars. This course focuses on using DAX (Data Analysis eXpressions) to create advanced calculations in Power Pivot data models. We will review what you learned in “Power BI—Go Beyond Pivot Tables with Power Pivot” and take your calculations to the next level using advanced DAX formulas. You will learn over 20 DAX functions that will allow you to perform calculations that were not possible with standard Excel®. We will also review the use of a date or calendar table that allows us to perform date analysis that was never possible before. This will allow us to use the new time-intelligent functions to perform complex calculations on our data like—month-to-date, quarter-to-date, year-to-date, last year same period, last year-to-date, etc. You will also learn the DAX calculation process in order to proof and validate your calculations. We will be using Power Pivot to create our DAX calculations, however, the process is very similar in Power BI Desktop and the functions and formulas are identical. If you are using Power BI Desktop, you should be able to follow along and learn how to create advanced calculations. This session is presented using Excel 2019/Office 365®. Regardless of the version you are using, most concepts covered in this course apply to all versions of Excel.
After attending this presentation, you will be able to* Create calculations using DAX formulas * Use a Date / Calendar table to perform complex date analysis * Use the DAX calculation process to validate calculations
The major topics that will be covered in this class include * Review Power Pivot calculations (column calculations vs. measures) * Create advanced DAX formulas * Using a Date / Calendar table for data analysis * The DAX calculation process * This course is No. 7 in the Microsoft® Power BI® series of webinars
Who Should Attend
Anyone who is using Power Pivot or Power BI® Desktop for data analysis
Attended the Power Pivot or Power BI® Desktop class or equivalent
Install Power Pivot (email: Po
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