About this course
The goal of the video course is to teach through examples of increasing complexity how to solve business scenarios by adapting the data model, so that the required DAX code becomes easier, faster and more robust. All the demos and the exercises are based on Power BI examples. The course is provided through the SQLBI online portal and made available by DataSF.
Length: The course is fully self-paced and online. It includes over 15 hours of recorded lectures, plus another 15-20 hours of individual exercises. You will have access to this course for two weeks.
What you’ll learn in this course
- Introduction to data modeling
- Header/detail tables
- Multiple fact tables
- Working with date and time
- Tracking historical attributes
- Using snapshots
- Analyzing date and time intervals
- Many-to-many relationships
- Working with different granularities
- Segmentation date models
- Working with multiple currencies
Prerequisites
Note: this is an advanced course and is geared towards Power BI users who are already familiar with intermediate topics such as data modeling and basic DAX expressions or familiarity with other coding/ programmatic languages (i.e. R, Python, SQL).
This course is aimed at users of Power BI Desktop or Power Pivot for Excel, and at Analysis Services developers who want to learn how to build the optimal data model for their reporting needs.
Completion of Data Academy’s Intro to PowerBI and Intermediate Power BI courses is required. This course assumes a good working knowledge of how PowerBI works. Heavy use is made of the query editor and familiarity is assumed. This course is not designed as a refresher course, but as the next stage in training for advanced Power BI analysts.
Upcoming courses scheduled
View the Course Calendar to see a list of upcoming classes. To get notified when enrollment opens for a class, complete the Course Interest Form and select the class (or classes) you’re interested in.
After completing the interest form, you will get an email when enrollment opens 3 weeks prior to class. Enrollment is not guaranteed as sometimes there are more interested employees than available seats.
Note: You must get your supervisor’s approval to attend any Data Academy courses.