DP-600 study plan

Week 1chapters 1–5 · about 11 hours Done

• Read these chapters:
  • 1. Microsoft Fabric for analytics engineers: platform, capacities and choosing a data store
  • 2. Workspace and item access control
  • 3. Row-, column-, object- and file-level security
  • 4. Governance: sensitivity labels, endorsement, lineage and impact analysis
  • 5. Version control, Power BI projects and deployment pipelines
• After each chapter, cover its key takeaways and explain each one out loud. Re-read any you can’t.
• Free study notes for this week: Choosing a Fabric data store: lakehouse, warehouse, eventhouse or SQL database, Microsoft Fabric workspace roles: Admin, Member, Contributor and Viewer, Fabric deployment pipelines: what gets copied and how deployment rules work.
• Look up any unfamiliar term in the DP-600 glossary.

Exam skill areas this week: Maintain a data analytics solution · 25–30%Prepare data · 45–50%Implement and manage semantic models · 25–30%

Week 2chapters 6–10 · about 12 hours Done

• Read these chapters:
  • 6. XMLA endpoint, shared semantic models and reusable assets
  • 7. Getting data into Fabric: connections, OneLake catalog, shortcuts and ingestion
  • 8. Lakehouses, Delta tables and Spark transformations
  • 9. Data warehouses and T-SQL in Fabric
  • 10. Star schemas and data preparation patterns
• After each chapter, cover its key takeaways and explain each one out loud. Re-read any you can’t.
• Free study notes for this week: Choosing a Fabric ingestion tool: Copy job, pipelines, Dataflow Gen2, notebooks or eventstreams, Fabric Warehouse vs lakehouse SQL analytics endpoint.
• Look up any unfamiliar term in the DP-600 glossary.

Exam skill areas this week: Maintain a data analytics solution · 25–30%Prepare data · 45–50%Implement and manage semantic models · 25–30%

Week 3chapters 11–15 · about 11 hours Done

• Read these chapters:
  • 11. Power Query, Dataflow Gen2 and the visual query editor
  • 12. Real-Time Intelligence and KQL
  • 13. Designing semantic models: storage modes, relationships and composite models
  • 14. DAX for analytics engineers
  • 15. Optimising enterprise semantic models: performance, Direct Lake and incremental refresh
• After each chapter, cover its key takeaways and explain each one out loud. Re-read any you can’t.
• Free study notes for this week: Choosing a Power BI storage mode: Import, DirectQuery, Dual or Direct Lake, Many-to-many relationships and bridge tables in Power BI, Direct Lake on OneLake vs Direct Lake on SQL analytics endpoint.
• Look up any unfamiliar term in the DP-600 glossary.

Exam skill areas this week: Prepare data · 45–50%Implement and manage semantic models · 25–30%

Week 4review Done

• Go back through every chapter’s key takeaways. Anything you can’t explain without looking, re-read that section.
• Re-read the common-trap callouts: they mark the answers that look right but aren’t.
• Check the exam coverage map against Microsoft’s own outline, in case it has changed since the book was checked.
• Take Microsoft’s free practice assessment, if your exam has one, from the official DP-600 study guide page. Revisit the chapters behind any weak area.
• Try the exam sandbox to get used to the exam’s screens and question formats.
• Get the free exam-day checklist and work through it a few days before your exam.

Week 1chapters 1–3 · about 6 hours Done

• Read these chapters:
  • 1. Microsoft Fabric for analytics engineers: platform, capacities and choosing a data store
  • 2. Workspace and item access control
  • 3. Row-, column-, object- and file-level security
• After each chapter, cover its key takeaways and explain each one out loud. Re-read any you can’t.
• Free study notes for this week: Choosing a Fabric data store: lakehouse, warehouse, eventhouse or SQL database, Microsoft Fabric workspace roles: Admin, Member, Contributor and Viewer.
• Look up any unfamiliar term in the DP-600 glossary.

Exam skill areas this week: Maintain a data analytics solution · 25–30%Prepare data · 45–50%Implement and manage semantic models · 25–30%

Week 2chapters 4–5 · about 4 hours Done

• Read these chapters:
  • 4. Governance: sensitivity labels, endorsement, lineage and impact analysis
  • 5. Version control, Power BI projects and deployment pipelines
• After each chapter, cover its key takeaways and explain each one out loud. Re-read any you can’t.
• Free study notes for this week: Fabric deployment pipelines: what gets copied and how deployment rules work.
• Look up any unfamiliar term in the DP-600 glossary.

Exam skill areas this week: Maintain a data analytics solution · 25–30%Prepare data · 45–50%

Week 3chapters 6–7 · about 5 hours Done

• Read these chapters:
  • 6. XMLA endpoint, shared semantic models and reusable assets
  • 7. Getting data into Fabric: connections, OneLake catalog, shortcuts and ingestion
• After each chapter, cover its key takeaways and explain each one out loud. Re-read any you can’t.
• Free study notes for this week: Choosing a Fabric ingestion tool: Copy job, pipelines, Dataflow Gen2, notebooks or eventstreams.
• Look up any unfamiliar term in the DP-600 glossary.

Exam skill areas this week: Maintain a data analytics solution · 25–30%Prepare data · 45–50%Implement and manage semantic models · 25–30%

Week 4chapters 8–9 · about 5 hours Done

• Read these chapters:
  • 8. Lakehouses, Delta tables and Spark transformations
  • 9. Data warehouses and T-SQL in Fabric
• After each chapter, cover its key takeaways and explain each one out loud. Re-read any you can’t.
• Free study notes for this week: Fabric Warehouse vs lakehouse SQL analytics endpoint.
• Look up any unfamiliar term in the DP-600 glossary.

Exam skill areas this week: Prepare data · 45–50%Implement and manage semantic models · 25–30%

Week 5chapters 10–11 · about 5 hours Done

• Read these chapters:
  • 10. Star schemas and data preparation patterns
  • 11. Power Query, Dataflow Gen2 and the visual query editor
• After each chapter, cover its key takeaways and explain each one out loud. Re-read any you can’t.
• Look up any unfamiliar term in the DP-600 glossary.

Exam skill areas this week: Prepare data · 45–50%

Week 6chapters 12–13 · about 4 hours Done

• Read these chapters:
  • 12. Real-Time Intelligence and KQL
  • 13. Designing semantic models: storage modes, relationships and composite models
• After each chapter, cover its key takeaways and explain each one out loud. Re-read any you can’t.
• Free study notes for this week: Choosing a Power BI storage mode: Import, DirectQuery, Dual or Direct Lake, Many-to-many relationships and bridge tables in Power BI.
• Look up any unfamiliar term in the DP-600 glossary.

Exam skill areas this week: Prepare data · 45–50%Implement and manage semantic models · 25–30%

Week 7chapters 14–15 · about 5 hours Done

• Read these chapters:
  • 14. DAX for analytics engineers
  • 15. Optimising enterprise semantic models: performance, Direct Lake and incremental refresh
• After each chapter, cover its key takeaways and explain each one out loud. Re-read any you can’t.
• Free study notes for this week: Direct Lake on OneLake vs Direct Lake on SQL analytics endpoint.
• Look up any unfamiliar term in the DP-600 glossary.

Exam skill areas this week: Prepare data · 45–50%Implement and manage semantic models · 25–30%

Week 8review Done

• Go back through every chapter’s key takeaways. Anything you can’t explain without looking, re-read that section.
• Re-read the common-trap callouts: they mark the answers that look right but aren’t.
• Check the exam coverage map against Microsoft’s own outline, in case it has changed since the book was checked.
• Take Microsoft’s free practice assessment, if your exam has one, from the official DP-600 study guide page. Revisit the chapters behind any weak area.
• Try the exam sandbox to get used to the exam’s screens and question formats.
• Get the free exam-day checklist and work through it a few days before your exam.