Exam DP-600: Microsoft Fabric Analytics Engineer Associate Certification Bootcamp

Instructor: Ashraf Ghonaim · Language: English or Arabic · Suggested duration: 4 days · Level: Advanced Certification Track (Level 300)

Official exam: DP-600 (Implementing Analytics Solutions Using Microsoft Fabric)

Objectives

• Master every objective tested on the official Microsoft DP-600: Fabric Analytics Engineer Associate exam.
• Ingest, transform, and model enterprise data across Fabric Lakehouses, Data Warehouses, Dataflows Gen2, Pipelines, Notebooks (PySpark), and T-SQL.
• Design, optimize, and manage large-scale Direct Lake and Composite enterprise Semantic Models using .pbip, TMDL, Tabular Editor, and DAX Studio.
• Implement end-to-end lifecycle management (Git CI/CD, Deployment Pipelines), security (OneLake RBAC, RLS, CLS, OLS, Dynamic Data Masking), and governance.

Outline and contents (Mapped to Official Microsoft DP-600 Exam Domains)

1. Domain 1: Maintain a Data Analytics Solution (25–30%)
   • Implementing security and governance: Workspace roles, item-level permissions, OneLake data access roles, RLS, Column-Level Security (CLS), Object-Level Security (OLS), and Dynamic Data Masking
   • Configuring Microsoft Purview sensitivity labels, endorsement badges (Promoted, Certified, Master Data), and analyzing workspace lineage
   • Implementing lifecycle management: Power BI Project (.pbip), TMDL, Git integration (branching, pull requests, syncing), Fabric Deployment Pipelines, and deployment rules
   • Configuring XMLA endpoint settings and managing capacity/workspace monitoring
2. Domain 2: Prepare Data (45–50%)
   • Creating and managing data connections, OneLake Shortcuts (ADLS Gen2, S3, Dataverse, internal OneLake), Lakehouses, and Data Warehouses
   • Copying and orchestrating data with Data Pipelines, Copy Activity, and Dataflows Gen2 (staging vs. non-staging destinations)
   • Designing and implementing Medallion architectures (Bronze, Silver, Gold) and Star Schema dimensional models (including Slowly Changing Dimensions Type 1 & Type 2)
   • Transforming and querying data using T-SQL (CTEs, window functions, MERGE, views, stored procedures), PySpark (DataFrames, Spark SQL, Delta table operations), and Power Query M
   • Optimizing Lakehouse/Warehouse performance: V-Order, OPTIMIZE file compaction, VACUUM retention, and handling slowly changing/late-arriving data
3. Domain 3: Implement and Manage Semantic Models (25–30%)
   • Designing and building large-scale semantic models: choosing storage modes (Direct Lake, Import, DirectQuery, Composite), Star Schema relationships, and bridge tables
   • Implementing advanced semantic model features: Calculation Groups, Dynamic Format Strings, Field Parameters, Perspectives, and Composite Model aggregations
   • Understanding Direct Lake framing, Delta table guardrails, and configuring fallback behavior (DirectLakeBehavior)
   • Writing complex DAX calculations (iterators, window functions, custom time intelligence, semi-additive measures)
   • Optimizing and troubleshooting semantic models using Performance Analyzer, DAX Query View, DAX Studio (VertiPaq Analyzer & Server Timings), and Tabular Editor (Best Practice Analyzer)
4. DP-600 Exam Cram & Case Study Simulation (Led by Ashraf Ghonaim)
   • Architectural decision matrices (When to choose Dataflow Gen2 vs. Pipeline vs. Notebook; Lakehouse vs. Warehouse; Direct Lake vs. Import)
   • Code-completion drills across DAX, T-SQL, and PySpark
   • Full-length timed DP-600 mock exam and detailed walkthrough

Target audience

Power BI developers, analytics engineers, BI architects, and data engineers seeking to earn the Microsoft Certified: Fabric Analytics Engineer Associate (DP-600) credential.

Expected outcomes

Participants master multi-engine analytics engineering across SQL, Spark, Power Query, and DAX within Microsoft Fabric and achieve full exam readiness for DP-600.