Fabric Analytics Engineering: End-to-End Enterprise Solution

Instructor: Alaa Hady · Language: English or Arabic · Suggested duration: 3–4 days · Level: Advanced (Level 300)

Objectives

• Design, build, and deploy an end-to-end enterprise analytics solution in Microsoft Fabric.
• Integrate Lakehouses, Warehouses, Dataflows Gen2, Pipelines, PySpark/T-SQL, and Direct Lake Semantic Models.
• Implement data quality validation, workspace security, and enterprise lifecycle management (.pbip, Git integration, Deployment Pipelines).
• Present a working prototype architecture and production handover plan.

Outline and contents

1. Requirements analysis, source system assessment, and architecture pattern selection (Lakehouse vs. Warehouse)
2. Workspace topology, domain assignment, and solution setup
3. Metadata-driven data ingestion and pipeline orchestration
4. Designing and building Bronze, Silver, and Gold Medallion layers
5. Engineering transformations and data quality rules in T-SQL, PySpark, and Dataflows Gen2
6. Authoring Direct Lake Semantic Models, Calculation Groups, and business DAX measures
7. Power BI executive reporting and self-service consumption
8. Defence-in-depth security: Workspace roles, OneLake RBAC, RLS, CLS, and OLS
9. CI/CD lifecycle: Git integration (.pbip/TMDL), Fabric Deployment Pipelines, and operational monitoring
10. Capstone Demonstration & Architecture Design Review

Target audience

Experienced BI developers, analytics engineers, data engineers, and solution architects leading corporate Fabric implementations.

Expected outcomes

Participants build a complete production-grade Fabric architecture from scratch and document its governance and deployment model. (Note: Learners seeking dedicated exam preparation for Microsoft Exam DP-600 should also see Course 46 in Academy G).