DP-600 prerequisites: what you need first
DP-600 has no formal prerequisite: Microsoft does not require another certification or course before you book it. The exam does assume working knowledge, though. The audience profile expects you to query and analyse data with SQL, KQL and DAX, and to have experience designing, creating and managing analytical assets such as semantic models, warehouses and lakehouses. This page turns that into a checklist you can test yourself against.
What Microsoft says about the role
The official audience profile describes a candidate with subject matter expertise in designing, creating and managing analytical assets. Your responsibilities include preparing and enriching data for analysis, securing and maintaining analytics assets, and implementing and managing semantic models. You work with stakeholders on business requirements and partner with architects, analysts, engineers and administrators. You should be able to query with SQL, KQL and DAX.
Skills checklist
| Area | You should be able to | If not, start with |
|---|---|---|
| SQL | Write joins, grouping, window functions and views | Any T-SQL tutorial, then practise in a Fabric warehouse |
| DAX | Write a measure using CALCULATE, a variable and an iterator | The Power BI modelling modules on Microsoft Learn |
| Power BI | Build a model with relationships and publish it | PL-300 material |
| Data modelling | Explain fact tables, dimensions and a star schema | Any dimensional modelling primer |
| Fabric | Create a workspace, lakehouse, warehouse and pipeline | The free Fabric trial and Learn modules |
| KQL | Filter and summarise a table | The KQL quick-start in Microsoft documentation |
| Governance | Explain workspace roles and sensitivity labels | Microsoft Fabric security documentation |
Helpful but not required
- PL-300 (Power BI Data Analyst). It teaches Power Query, modelling and DAX at the report-author level. It is not required, but if DAX or model design is new to you, the skills carry directly into DP-600’s semantic model domain.
- DP-700 (Fabric Data Engineer). Useful if you want the data-engineering side as well; see DP-600 vs DP-700.
- Python or PySpark basics. The audience profile for DP-600 names SQL, KQL and DAX, not PySpark, but notebook-based questions about a lakehouse can still appear, so read PySpark snippets comfortably.
- Git basics. Branching and merging are part of the development lifecycle objectives.
What access you need to practise
You will learn faster with your own environment than from reading. Fabric needs a capacity, which can be a trial. Check the current trial terms on the Microsoft site before relying on one, because they change. You also need Power BI Desktop (free, Windows) to work with .pbip projects and semantic models. A Microsoft Learn profile is needed to book and later to renew.
What comes after DP-600?
The Fabric Analytics Engineer Associate is an intermediate, role-based credential. Which exam to take next depends on your direction: DP-700 for the data-engineering side, or PL-300 if you want the Power BI analyst credential. The certification costs guide helps you plan the budget.
Quick self-test
If you can do all of these, you can start the study plan at full speed:
- Create a star schema from a flat table in T-SQL.
- Write a measure that returns sales for the same period last year.
- Explain what the difference is between a workspace Viewer and an item-level share.
- Say when a lakehouse is a better choice than a warehouse.
- Describe what happens in a deployment pipeline when you promote content from test to production.
If you miss two or more, add a week of fundamentals before the four-week plan. Next: exam tips.