Description
This course is designed for professionals who want to take their skills in Power BI to the next level. The course dives deeper into the advanced aspects of Power BI, with a strong focus on query editing and data modeling. Participants will learn to perform complex data analysis, write custom query functions, and apply advanced data modeling strategies. We build on the basic knowledge gained in “Power BI: Core Features 1” providing participants with the tools and techniques needed to develop more efficient and effective BI solutions.
Objectives
After completing this Power BI course, you will be able to:
- Use functions in the query editor that are not available through the interface
- Write your own query functions
- Use parameters in queries
- Point out the advantages/differences between a star scheme and a snowflake scheme
- Optimize a model
Target Group
This course is designed for professionals who already have a basic knowledge of Power BI, for example, through attending the course “Power BI: Core Features 1” or through relevant work experience. It is ideal for those who want to expand their skills in data modeling and query processing to be able to perform more complex analysis and reporting.
Prerequisites
You have attended the course “Power BI: Core Features 1” or have a solid basic knowledge of Power BI.
Contents
Part 1 Power Query
- Pro and con of the different connection types: import, direct connection and live connection
- Defining parameters
- Query folding
- Introduction to M: the language of Power Query (define constant values, generate lists, use of functions not accessible through the interface, references to other steps or queries)
- Generating dynamic date table
Part 2 Data Modeling
- Star schema versus Snowflake schema
- Relationships between tables (single versus cross-filtering, active versus non-active relationships)
- Model optimization (Vertipaq engine /xVelocity in-memory analytical engine, setting custom sort order, data categories, default summarizations….
- Defining hierarchies
- Composite models
- When to use multiple date tables?