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Exam Information
Official specifications published by Microsoft
Exam Format
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Skills this practice test covers
- Secure Fabric items with workspace roles, item permissions, row-level security and sensitivity labels.
- Manage version control, .pbip projects and deployment pipelines for a Fabric workspace.
- Choose between a lakehouse, a warehouse and an eventhouse for a given data need.
- Build a star schema with views, functions and stored procedures, and clean duplicates and nulls.
- Select, filter and aggregate data with SQL, KQL and the Visual Query Editor.
- Write DAX with variables and iterators, and tune semantic models that use Direct Lake.
Explore related topics
DP-600 exam content
3 domains · 12 topics · 205 of 209 questions sorted by domain
Maintain a data analytics solution54 questions
This domain covers keeping a Fabric analytics solution secure and under control. Candidates set access from workspace level down to rows, columns, objects and files, label and endorse items, and manage the development lifecycle with Git, .pbip projects and deployment pipelines.
Skills tested
- Assign workspace roles and item-level permissions for different groups of users.
- Implement row-level, column-level, object-level and file-level access control.
- Apply sensitivity labels to items and endorse the items that users should trust.
- Configure version control for a workspace and manage a Power BI Desktop project (.pbip).
- Run impact analysis on downstream items, and deploy semantic models through the XMLA endpoint.
Questions by topic
- Implement security and governance23
- Maintain the analytics development lifecycle31
Prepare data100 questions
The largest domain covers getting data into Fabric and shaping it for analysis. Candidates connect to and discover data, choose a lakehouse, warehouse or eventhouse, transform data into a star schema, and query it with SQL, KQL or the Visual Query Editor.
Skills tested
- Discover data with the OneLake data hub and the real-time hub.
- Choose a lakehouse, warehouse or eventhouse, and set up OneLake integration for an eventhouse.
- Create views, functions and stored procedures, and implement a star schema.
- Resolve duplicate data, missing data and null values, and convert column data types.
- Merge, join, denormalize and aggregate data for reporting.
Questions by topic
- Transform data32
- Query and analyze data19
- Get data28
- Implement a star schema for a lakehouse or warehouse7
- Choose between a lakehouse, warehouse, or eventhouse4
- Create objects in a lakehouse or warehouse7
- Maintain the analytics development lifecycle3
Implement and manage semantic models51 questions
This domain covers the models that Power BI reports read. Candidates choose a storage mode, design relationships and DAX calculations, and keep large models fast with Direct Lake, incremental refresh and DAX tuning.
Skills tested
- Choose between Import, DirectQuery and Direct Lake storage modes.
- Implement bridge tables and many-to-many relationships, and design composite models.
- Write DAX with variables, iterators, table filtering, windowing and information functions.
- Add calculation groups, dynamic format strings and field parameters.
- Configure Direct Lake fallback and refresh, and implement incremental refresh.
Questions by topic
- Design and build semantic models30
- Optimize enterprise-scale semantic models18
- Implement security and governance3
Requirements
- No formal prerequisites: anyone can book the exam.
- Recommended: skills like those of Power BI Data Analyst, the background Microsoft's DP-600 course is written for.
- Recommended: hands-on work designing and managing semantic models, data warehouses or lakehouses.
- Recommended: the ability to query and analyze data with SQL, KQL and DAX.
About the DP-600 exam
Analytics engineers who prepare data and build semantic models in Microsoft Fabric take DP-600 to earn Microsoft Certified: Fabric Analytics Engineer Associate. Preparing data in lakehouses, warehouses and eventhouses is the largest part of the exam. The rest covers semantic models for Power BI, and the security, governance and lifecycle work that keeps a solution maintained. Candidates query data with SQL, Kusto Query Language (KQL) and Data Analysis Expressions (DAX).
Prepare data has the most questions in the PlanetCert practice test, as it has the most weight on the exam. The explanations show why one store fits a scenario: a warehouse for teams that write T-SQL, a lakehouse for Spark notebooks, or an eventhouse for KQL over streaming data. Study Mode suits the semantic model questions, where storage modes and Direct Lake fallback need a careful read. Brainy AI Assistant can step through a DAX measure line by line, or explain how a deployment pipeline moves content between stages.
How to earn the certification
- Earns
- Microsoft Certified: Fabric Analytics Engineer AssociateAssociate
The certification is valid for one year, and holders renew it each year with a free online assessment on Microsoft Learn.
- Before
- PL-300 Power BI Data Analyst
Optional. Microsoft's DP-600 course is written for data professionals with skills like those this certification covers.
- DP-900 Azure Data Fundamentals
Optional. A fundamentals exam on core data concepts, for those who are new to data work.
- PL-300 Power BI Data Analyst
How to prepare for DP-600
- 1
Load one dataset into three stores
In a Fabric trial workspace, load the same small dataset into a lakehouse, a warehouse and an eventhouse. Note which tools and query languages each item offers, since the exam asks when to choose each one.
- 2
Shape a star schema in T-SQL
Prepare data carries the most weight. In the warehouse, build fact and dimension tables with views and stored procedures, and fix duplicates, missing values and wrong data types on the way.
- 3
Model the same tables three ways
Connect one semantic model to the tables in Import, DirectQuery and Direct Lake modes. Compare how each one refreshes, and find what makes Direct Lake fall back to DirectQuery.
- 4
Lock down and ship a workspace
Add workspace roles, row-level security and a sensitivity label. Then connect the workspace to Git, save a report as a .pbip project, and promote it through a deployment pipeline.
- 5
Drill DAX before the timed runs
Work through the DP-600 practice test in Study Mode, with extra time on DAX variables, iterators and calculation groups. Finish with full runs in Timed Mode, and ask Brainy AI Assistant to walk through each missed DAX question.
Start a timed DP-600run
Microsoft's course is DP-600T00-A: Microsoft Fabric Analytics Engineer. Its learning paths are Get started with Microsoft Fabric, Implement a data warehouse with Microsoft Fabric, Work with semantic models in Microsoft Fabric, and Administer and govern Microsoft Fabric.
Who DP-600 is for
- Power BI developers who now build reports on lakehouses and warehouses in Microsoft Fabric.
- BI professionals who design and own semantic models for a whole organization.
- Data engineers who are moving into analytics and model design.
Typical job titles: Analytics engineer · Power BI developer · BI developer · Data analyst · BI architect
DP-600 glossary
19 terms from the exam objectives and the vendor's official material, each defined in a sentence.
- Calculation groups
- A model feature that applies one DAX pattern, such as year-to-date, to many measures at once.
- Deployment pipelines
- A Fabric feature that moves content through stages, such as development, test and production workspaces.
- Direct Lake
- A storage mode in which a semantic model reads table files in OneLake directly, without importing a copy.
- DirectQuery
- A storage mode that sends each report query to the source instead of storing data in the model.
- Dynamic format strings
- Formats written as DAX expressions, so that a measure can change how it is displayed by context.
- Endorsement
- Marking an item as promoted or certified, so that users can find content they can trust.
- Eventhouse
- A Fabric item for real-time and time-series data that holds one or more KQL databases.
- Field parameters
- A Power BI feature that lets report users switch the measure or column that a visual shows.
- Import mode
- A storage mode that loads a copy of the data into the model, so queries are fast but the data must be refreshed.
- Incremental refresh
- A refresh policy that reloads only recent or changed data instead of the whole table.
- Lakehouse
- A Fabric item that holds files and tables together in OneLake, worked on mainly with Spark notebooks and a SQL endpoint.
- OneLake
- The single data lake for a Microsoft Fabric tenant, where lakehouses, warehouses and other items keep their data.
- Power BI Desktop project (.pbip)
- A way of saving a Power BI report and model as folders of text files, so that Git can track every change.
- RLS (Row-Level Security)
- Rules that filter which rows of data each user can see.
- Sensitivity labels
- Microsoft Purview labels that mark how confidential an item is, so that protection rules can follow its data.
- Star schema
- A design with fact tables of events in the center and dimension tables that describe them around it.
- Visual Query Editor
- A no-code query builder in Fabric for selecting, filtering and aggregating data.
- Warehouse
- A Fabric item for relational data that can be read and changed with T-SQL, including stored procedures.
- XMLA endpoint
- A connection point that lets tools such as Tabular Editor read, change and deploy a semantic model.