Importing & Shaping Data from the raw data sources is the first stage of building a Power BI Reporting Solution. Once the data has been cleansed, validated, transformed and integrated the data modelling process starts.
PowerQuery/Query Editor will provide us with reliable and quality data sets that we can now feed into a tabular model. The role of the Tabular Model is to allow the definition of relationships between the prepared datasets, the creation of hierarchies that mirror how users will wish to drill down into or rollup business entities, and the creation of business calculations (measures/key performance indicators (KPIs)) to represent all values that are to be reported on.
The Tabular Model provides for a central, approved, "one truth" representation of all business data, enabling fields to be drag and dropped into visualisations without having to define complex relationships and expressions to define calculation logic.
This 2 day Advanced Power BI course builds on the foundation Power BI knowledge introduced in the Introduction To Power BI course to provide an in depth coverage of the more advanced Tabular Modelling techniques. You will look at the typical challenges that may face you when Queries are imported into a Tabular Model, you will learn about advanced relationships, filter contexts and Cross Filter Direction, as well using the DAX expression Language to create simple and complex business calculations. The course will introduce best practices in data modelling architecture and layout to ensure that you get the best design for your Power BI report and dashboard needs.
Delegates should ideally have previously attended the Introduction to Power BI course or have an equivalent knowledge. There is no need to have an in depth knowledge of Query Editor for this course, but you will find it beneficial to learn about Query Editor (PowerQuery) and all that it offers in order to plan and design the most effective Tabular Model for your business requirement.
Set Column data Types
Add New Columns
Tables & Filters
Star and Snowflake Schemas
Multiple Fact Tables
Date & Time Dimensions
Cardinality: One to One, One to many, many to One, Many to Many