The Power BI training assumes some familiarity with relational databases. Otherwise, you’ll have difficulty understanding what you’re doing when you go through the steps to create a data model.
You should also have a basic understanding of the difference between on-premise and cloud computing. This will give you the context to understand the interaction between Power BI Desktop and the Power BI service, as well as the purpose of the Power BI Gateway.
When connecting to a database, Power BI gives you the option of pulling in entire database tables or writing SQL queries. If you’re not yet familiar with SQL, you should go through a few hours of hands-on training before starting on Power BI.
It’s not a requirement, but the more experience you have with other Microsoft data analysis tools the easier time you’ll have learning Power BI.
- SQL Analysis Services and Power Pivot both use a language called DAX. Power BI also uses DAX. So, if you’ve already learned DAX through using other Microsoft software, you’ll have a big advantage.
- Power Query is used by Azure Data Lake Storage, Microsoft Dataverse, Excel. And it’s also used by Power BI. So, again, prior experience with Power Query will give you a head start when learning Power BI.
I don’t think it’s necessary to understand Azure or have experience with SQL Analysis Services to learn Power BI, though those things probably help.