Understanding the basics of Power BI can only get you so far. There are many lesser known advanced features within the tool that can take your Power BI knowledge to the next level. This course explores those features. Starting with how the languages of R and M can be used to extend that standard data extraction and transformation capabilities of Power BI. You will then understand complex data modeling scenarios and how Power BI can overcome them. Lastly, you will learn about several advanced data visualization techniques that can take your reports and dashboards beyond the basics.
Overview
COURSE DIFFICULTY
COURSE DURATION
7h 33m
Skills Learned
After completing this online training course, students will be able to:
Write advanced DAX formulas using CALCULATE and filter context
Implement time intelligence calculations for period comparisons
Configure row-level security using DAX expressions
Use variables to simplify and optimize DAX formulas
BI Developers, Data Analysts
Basic Power BI knowledge
01. Advanced Power BI - What you need to get started
02. Getting Started
03. R Integration (Installation and Configuration)
04. R Integration (R Scripting Basics)
05. R Integration (R for Data Cleansing)
06. Python Integration (Installation and Configuration)
07. Python Integration (Python as a Data Source)
08. Python Integration (Python Visual)
09. M Query (Variables and Parameters)
10. M Query (Expanding Lists)
11. Query Folding (Basics)
12. Query Folding (Beyond the Basics)
13. Advanced Data Modeling (Filtering)
14. Advanced Data Modeling (Cross-Filtering and Time Intelligence)
15. Advanced Data Modeling (Many to Many with DAX)
16. Advanced Data Modeling (Creating a Bridge Table)
17. Advanced Data Modeling (Role Playing Tables with DAX)
18. Advanced Data Modeling (Role Playing Tables without DAX)
19. Advanced Data Modeling (Mismatched Granularities)
20. Advanced Data Modeling (Weighted Allocation)
21. xVelocity (Overview)
22. xVelocity (Vertipaq Analyzer and DAX Studio)
23. xVelocity (Column Cardinality)
24. xVelocity (Calculated Columns)
25. Advanced Visualizations (Visuals with DAX)
26. Power BI Administration (Incremental Refresh)
27. Power BI Administration (Implementing Row Level Security)
28. Power BI Administration (Implementing Dynamic Security)
29. Power BI Administration (Power BI Embedded)
30. Outro
SKILLS LEARNED
Skills Learned
After completing this online training course, students will be able to:
Write advanced DAX formulas using CALCULATE and filter context
Implement time intelligence calculations for period comparisons
Configure row-level security using DAX expressions
Use variables to simplify and optimize DAX formulas
WHO SHOULD ATTEND
BI Developers, Data Analysts
PREREQUISITES
Basic Power BI knowledge
COURSE OUTLINE
01. Advanced Power BI - What you need to get started
02. Getting Started
03. R Integration (Installation and Configuration)
04. R Integration (R Scripting Basics)
05. R Integration (R for Data Cleansing)
06. Python Integration (Installation and Configuration)
07. Python Integration (Python as a Data Source)
08. Python Integration (Python Visual)
09. M Query (Variables and Parameters)
10. M Query (Expanding Lists)
11. Query Folding (Basics)
12. Query Folding (Beyond the Basics)
13. Advanced Data Modeling (Filtering)
14. Advanced Data Modeling (Cross-Filtering and Time Intelligence)
15. Advanced Data Modeling (Many to Many with DAX)
16. Advanced Data Modeling (Creating a Bridge Table)
17. Advanced Data Modeling (Role Playing Tables with DAX)
18. Advanced Data Modeling (Role Playing Tables without DAX)
19. Advanced Data Modeling (Mismatched Granularities)
20. Advanced Data Modeling (Weighted Allocation)
21. xVelocity (Overview)
22. xVelocity (Vertipaq Analyzer and DAX Studio)
23. xVelocity (Column Cardinality)
24. xVelocity (Calculated Columns)
25. Advanced Visualizations (Visuals with DAX)
26. Power BI Administration (Incremental Refresh)
27. Power BI Administration (Implementing Row Level Security)
28. Power BI Administration (Implementing Dynamic Security)
29. Power BI Administration (Power BI Embedded)
30. Outro
