Microsoft Fabric for Power BI Analysts

What's inside

1. Level 1: What Fabric Is and How It Extends Power BIFree
   Learn how Microsoft Fabric puts Power BI alongside data engineering, data warehousing, data science and Real-Time Intelligence on one SaaS platform with shared OneLake storage, and what that changes for a Power BI analyst.
2. Level 2: Capacities, SKUs, Trials and What Costs MoneyFree
   Learn how F SKU capacities, measured in capacity units (CUs), pay for Fabric compute, how OneLake storage is billed separately, how the Fabric trial works, and where Power BI Pro or PPU licences still matter, checking every figure against Microsoft's current pages.
3. Level 3: Workspaces and Domains for the Sales Solution
   Create the trial workspace the course builds in, assign it to the trial capacity, and see how domains group workspaces by business area for discovery and governance.
4. Level 4: OneLake, Shortcuts and Mirroring in Outline
   Understand OneLake as the single tenant-wide data lake behind every Fabric item, how shortcuts point at data without copying it, and an outline of what mirroring does for operational databases.
5. Level 5: Lakehouse vs Warehouse vs Eventhouse
   Compare the three main data stores in Fabric (the lakehouse for files and Spark, the warehouse for T-SQL, the Eventhouse for KQL over streaming and time-series data) and learn a simple rule for which one fits each job.
6. Level 6: Delta Tables and the SQL Analytics Endpoint
   Load the sales CSV files into a lakehouse as Delta tables and query them read-only with T-SQL through the SQL analytics endpoint that Fabric creates automatically.
7. Level 7: Medallion Layers in Plain Terms
   Organise the sales data into bronze (raw), silver (cleaned) and gold (business-ready) layers, and decide which Fabric items hold each layer.
8. Level 8: Getting Data with Dataflows Gen2
   Use Dataflows Gen2, which is the Power Query you already know, to clean the sales data and load it into the silver lakehouse through a data destination.
9. Level 9: Notebooks and Spark: an Analyst's Outline
   Get a working outline of Fabric notebooks and Spark: read a Delta table, make a simple change in PySpark or Spark SQL, and write a silver table, so you can read and adjust what engineers build.
10. Level 10: Scheduling the Load with Data Pipelines
    Run the dataflow and notebook in order from a Fabric data pipeline, with dependencies, a schedule and failure handling, so the sales data refreshes without anyone clicking a button.
11. Level 11: Gold-Layer T-SQL Views in a Warehouse
    Create a Fabric warehouse for the gold layer, query the silver lakehouse tables across databases, and publish T-SQL views that shape a star schema for reporting.
12. Level 12: Building a Direct Lake Semantic Model
    Create a Direct Lake semantic model over the gold Delta tables, set up relationships and measures, and learn how Direct Lake reads Delta data straight from OneLake without an import.
13. Level 13: Direct Lake Fallback, Framing and Refresh
    Learn what happens behind a Direct Lake model: framing, refresh, transcoding into memory, and the guardrails that trigger fallback to DirectQuery or stop queries altogether.
14. Level 14: When Import or DirectQuery Is Still Better
    Weigh Direct Lake against Import, DirectQuery and composite models on latency, freshness, data size, DAX features, calculated columns and cost, and pick the right mode for each scenario.
15. Level 15: Finishing the End-to-End Sales Report
    Build and publish the Power BI sales report on the Direct Lake model, test it end to end from a new file landing to updated visuals, and share it with consumers through an app.
16. Level 16: Version Control with Git and Deployment Pipelines
    Connect the workspace to Git (Azure DevOps or GitHub) for version control, and promote items from dev to test to prod with deployment pipelines and deployment rules.
17. Level 17: Security: Workspace Roles, Item Permissions, OneLake
    Secure the solution with workspace roles, item-level sharing and permissions, SQL and semantic model security, and an outline of OneLake security, giving each person only what they need.
18. Level 18: Monitoring Capacity Use and Cost
    Use the Fabric Capacity Metrics app and the Monitoring hub to see which items burn CUs, understand smoothing, bursting and throttling, and keep the sales solution within budget.
19. Level 19: Real-Time Intelligence and Certifications
    Get an outline of Real-Time Intelligence (eventstreams, Eventhouse with KQL, Real-Time dashboards and Activator) and see where the DP-600 and DP-700 exams fit your learning path.
20. Level 20: Final Challenge: Review the Whole Sales Solution Exam
    Review and defend the whole solution from start to finish (capacity, workspace, OneLake, the medallion layers, the dataflow, notebook and pipeline loads, warehouse views, the Direct Lake model, report, Git, security and monitoring) and fix the weaknesses you find.

Access

The first 2 levels are free with a free account. Every level, the podcast edition and the AI tutor come with All Access at £4.99/month or any Creator plan — see pricing.

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