DP-600 Microsoft Fabric Analytics Engineer Exam Prep

What you'll learn

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Configure Fabric workspace roles, item permissions, and OneLake data access roles
Apply row-level, column-level, object-level security and dynamic data masking
Choose between Dataflows Gen2, pipelines, notebooks, and OneLake shortcuts for ingestion
Decide when to build a lakehouse vs a warehouse for a given analytics workload
Requirements

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Comfort with basic SQL (SELECT, JOIN, WHERE) and Power BI / DAX fundamentals
Description

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This course contains the use of artificial intelligence.
This course delivers exam-focused preparation for the DP-600 Microsoft Certified: Fabric Analytics Engineer Associate exam, built around Microsoft's current three-domain skills-measured outline: Maintain a data analytics solution, Prepare data, and Implement and manage semantic models. Instructor Aseem Mankotia walks through every domain using exact current Fabric terminology - OneLake, lakehouse, warehouse, the SQL analytics endpoint, Dataflows Gen2, data pipelines, notebooks and PySpark, Real-Time Intelligence with KQL, semantic models, Direct Lake vs Import vs DirectQuery, deployment pipelines, Git integration, and Copilot in Fabric - so you study the vocabulary the exam actually uses, not retired terms from the old four-domain outline still floating around older blogs.
Each chapter maps directly to an exam domain and weight range, highlights heavily-tested concepts, and pairs every idea with a read-and-understand Fabric walkthrough: configuring workspace roles and OneLake data access roles, applying row-level and column-level security, building a lakehouse and a warehouse, transforming data in a Spark notebook, ingesting with Dataflows Gen2 and pipelines, querying with T-SQL and KQL, modeling a star schema, choosing a semantic model storage mode, writing DAX measures, and setting up a Git-connected deployment pipeline. Copilot in Fabric is shown throughout as an accelerator for transformations, DAX, and query generation - with explicit emphasis on verifying its output rather than trusting it blindly.
The final chapter runs a full timed exam simulation with a 100-minute pacing strategy that covers both the roughly 48 standalone questions and the roughly 11 case-study questions, plus practice questions and flashcards covering lakehouse vs warehouse, Dataflow Gen2 vs notebooks vs pipelines, Direct Lake vs Import vs DirectQuery, and RLS/OLS/CLS decisions. This course is designed for exam-focused preparation and does not promise any particular result; the DP-600 exam fee is approximately USD 165 and varies by region, renews annually via a free Microsoft Learn assessment, and candidates should always verify current pricing and exam details directly with Microsoft before scheduling.
AI content disclosure: This course was produced with the assistance of artificial intelligence tools. Lecture narration is AI-voice generated, and lecture scripts, slides, and practice questions were drafted with AI assistance, then reviewed and curated by the instructor for technical accuracy and alignment with the official DP-600 exam guide.
Who this course is for

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Analytics engineers, Power BI developers, and BI/data professionals on Microsoft Fabric who want exam-focused DP-600 preparation
Homepage

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