Are terms like “ETL,” “Translytical,” or “delta parquet” still fuzzy...and maybe a little intimidating? This session breaks down the core concepts behind Power BI and Microsoft Fabric using plain language and real business examples.

We’ll look at why each major part of the platform exists, the business problems it solves, and the tradeoffs to consider when choosing one tool or approach over another. Attendees will be encouraged to share examples from their own organizations to help connect concepts to real-world needs.

Topics include:

1. Foundational data concepts
- data types vs. data formats
- where the star schema comes from
- ETL vs. ELT vs. ELTL

2. Common sources of confusion in Power BI
- Power Query vs. DAX
- PBIX vs. PBIR
- Implicit vs. explicit measures
- Where new features like TMDL, ontologies, and translytical task flows solve emerging needs for Power BI users

3. How to choose the right Fabric component:
- OneLake ingestion options (mirroring, shortcuts, virtual tables, delta parquet);
- Where to store data (Eventhouse, Lakehouse, Warehouse, Cosmos DB, SQL DBs);
- How to ingest/transform data (Data Factory, Notebooks, Data Pipeline Gen2, SQL views)

You’ll leave with a practical mental model for navigating both Power BI and Fabric, so you’ll know what to explore first, what to use when, and how to map each tool to your business needs.