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Last Updated: Aug 21, 2026

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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-500

Microsoft DP-500 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Implement and manage a data analytics environment25–30%- Governance and lifecycle management
  • 1. Monitor usage and audit activity
  • 2. Apply data governance with Microsoft Purview
  • 3. Implement version control and CI/CD
  • 4. Configure tenant and workspace settings
- Manage Azure Synapse Analytics workspace and resources
  • 1. Monitor and optimize Synapse performance
  • 2. Provision and configure Synapse workspace
  • 3. Configure security and access control
  • 4. Manage SQL pools and Spark pools
- Manage Power BI Premium and scalability
  • 1. Implement deployment pipelines
  • 2. Configure large dataset storage
  • 3. Manage workspaces and datasets
  • 4. Provision and assign Premium capacity
Topic 2: Implement and manage data models25–30%- Design tabular data models
  • 1. Choose import, DirectQuery, or composite mode
  • 2. Implement row-level security
  • 3. Create relationships and hierarchies
  • 4. Define calculated tables and columns
- Use DAX for calculations
  • 1. Create measures and calculation groups
  • 2. Implement time intelligence
  • 3. Use advanced DAX patterns
  • 4. Optimize DAX query performance
- Optimize model performance
  • 1. Tune DirectQuery behavior
  • 2. Manage aggregations
  • 3. Reduce cardinality and data size
  • 4. Configure query reduction settings
Topic 3: Query and transform data20–25%- Ingest and process data in Azure Synapse
  • 1. Query data using serverless SQL pool
  • 2. Optimize query performance
  • 3. Load data into dedicated SQL pools
  • 4. Use Apache Spark for data transformation
- Transform data with Power Query
  • 1. Design scalable dataflows
  • 2. Handle complex data sources
  • 3. Manage parameters and functions
  • 4. Optimize query logic and performance
- Integrate data sources
  • 1. Implement incremental refresh
  • 2. Combine on-premises and cloud data
  • 3. Configure data privacy and security
Topic 4: Explore and visualize data20–25%- Deploy and distribute analytics solutions
  • 1. Embed reports in applications and portals
  • 2. Monitor report usage and health
  • 3. Manage app workspaces
  • 4. Publish and share content securely
- Enable advanced analytics
  • 1. Use AI visuals and insights
  • 2. Implement custom visuals using Python or R
  • 3. Integrate Azure Machine Learning models
- Build enterprise-scale reports
  • 1. Configure real-time refresh
  • 2. Implement custom visuals and interactivity
  • 3. Design for performance and accessibility
  • 4. Create paginated reports

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