DP-600 Guided Course

This guided course is for learners who want a structured path through Implementing Analytics Solutions Using Microsoft Fabric. Start with ordered lessons, answer exam-style questions, review explanations, and use Practice Mode afterward to test retention.

• Follow an ordered DP-600 course path instead of starting with random questions.
• Use source-backed scenarios to connect concepts to practical administration decisions.
• Review why the correct answer fits and why the distractors do not.
• Track course progress on this device and return to the next lesson later.
• Move from guided learning into Practice Mode when you are ready to check retention and speed.

The full course continues in order. These early lessons are crawlable here so you can see the shape of the path before the interactive course loads.

1. Lesson 1: Select, filter, and aggregate by using Visual Query Editor, SQL, KQL, and DAX
   Lesson 1 uses Select, filter, and aggregate by using Visual Query Editor, SQL, KQL, and DAX to connect Prepare data with Select, filter, and aggregate by using Visual Query Editor, SQL, KQL, and DAX.
2. Lesson 21: Implement workspace, item, row, column, object, and file access controls
   Lesson 21 uses Implement workspace, item, row, column, object, and file access controls to connect Maintain a data analytics solution with Implement workspace, item, row, column, object, and file access controls.
3. Lesson 39: Configure Git integration, PBIP projects, and deployment pipelines
   Lesson 39 uses Configure Git integration, PBIP projects, and deployment pipelines to connect Maintain a data analytics solution with Configure Git integration, PBIP projects, and deployment pipelines.
4. Lesson 56: Choose storage modes and implement star-schema relationships
   Lesson 56 uses Choose storage modes and implement star-schema relationships to connect Implement and manage semantic models with Choose storage modes and implement star-schema relationships.
5. Lesson 71: Choose Fabric data stores and implement OneLake integration
   Lesson 71 uses Choose Fabric data stores and implement OneLake integration to connect Prepare data with Choose Fabric data stores and implement OneLake integration.
6. Lesson 86: Create connections, discover data, and choose ingestion or access
   Lesson 86 uses Create connections, discover data, and choose ingestion or access to connect Prepare data with Create connections, discover data, and choose ingestion or access.
7. Lesson 101: Create SQL views, functions, procedures, and enrichment logic
   Lesson 101 uses Create SQL views, functions, procedures, and enrichment logic to connect Prepare data with Create SQL views, functions, procedures, and enrichment logic.
8. Lesson 116: Implement star schemas, denormalization, and aggregations
   Lesson 116 uses Implement star schemas, denormalization, and aggregations to connect Prepare data with Implement star schemas, denormalization, and aggregations.
9. Lesson 131: Optimize models with Direct Lake, DAX tuning, and incremental refresh
   Lesson 131 uses Optimize models with Direct Lake, DAX tuning, and incremental refresh to connect Implement and manage semantic models with Optimize models with Direct Lake, DAX tuning, and incremental refresh.
10. Lesson 143: Write DAX with variables, iterators, table filters, windowing, and information functions
    Lesson 143 uses Write DAX with variables, iterators, table filters, windowing, and information functions to connect Implement and manage semantic models with Write DAX with variables, iterators, table filters, windowing, and information functions.