Microsoft Fabric Fundamentals for Analytics Teams

Instructor: Alaa Hady · Language: English or Arabic · Suggested duration: 1 day · Level: Foundation to Intermediate (Level 100–200)

Objectives

• Navigate the unified Microsoft Fabric experience, workspaces, and item types confidently.
• Understand how OneLake stores data once in open Delta Parquet format for all compute engines.
• Compare and select the right Fabric workload (Dataflows Gen2, Pipelines, Lakehouse, Warehouse, Notebooks, Semantic Models).
• Build a foundational end-to-end mini-pipeline from raw file ingestion to a Direct Lake Power BI report.

Outline and contents

1. The Microsoft Fabric architecture: SaaS unification, Personas, Workspaces, and OneLake
2. OneLake deep dive: open Delta Parquet format, OneLake File Explorer, and Shortcuts (zero-copy virtualization to ADLS Gen2, S3, Dataverse)
3. Ingestion options compared: Copy Job, Data Pipelines, Dataflows Gen2, and Mirroring
4. Analytical storage compared: Fabric Lakehouse (Spark + SQL analytics endpoint) vs. Fabric Data Warehouse (full T-SQL transactional engine)
5. Transformation choices: Low-code (Power Query), SQL (T-SQL procedures/views), and Pro-code (PySpark Notebooks)
6. Semantic Models & Direct Lake: how Power BI reads Delta tables directly from OneLake without scheduled imports
7. Governance, Domains, Purview Hub, and F-SKU capacity fundamentals
8. Hands-on Guided Lab: Ingesting raw data into a Lakehouse, transforming to a Gold table, and building a Direct Lake Power BI report

Target audience

Power BI developers, data analysts, IT professionals, data engineers, and analytics teams starting their Fabric journey.

Expected outcomes

Participants gain hands-on familiarity with the Fabric portal, understand how all workloads interconnect over OneLake, and can choose the right architecture pattern for their team's skill set.