Microsoft Fabric Data Engineer AssociateStudy guide
The associate certification for implementing data engineering with Microsoft Fabric (DP-700).
About Microsoft Fabric Data Engineer Associate (DP-700)
Microsoft Fabric Data Engineer Associate (DP-700) is a Associate-level certification from Microsoft. This page organizes the exam scope into a 3-chapter, 7-section study guide and lets you check your understanding with exam-style practice questions. A good flow is to read the chapters below in order, then test yourself via "Practice questions."
Exam domains (approximate weighting)
- Implement and manage an analytics solution~34%
- Ingest and transform data~33%
- Monitor and optimize an analytics solution~33%
Weights are approximate guidance for the live exam. Each domain is covered in detail in the chapters and sections below.
Official exam information: https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-700
1Implement and Manage an Analytics Solution (Fabric Basics)
- 1.1Overview of Microsoft Fabric
Understand Microsoft Fabric as a single SaaS unifying data integration, analytics, and BI, plus workspaces, capacity, and its experiences (Data Engineering, Data Factory, Data Warehouse, Real-Time, Power BI). The starting point for DP-700.
- 1.2OneLake and Data Stores (Lakehouse, Warehouse)
Understand OneLake (the single shared storage; Delta/Parquet, shortcuts) and the two main data stores—Lakehouse and Warehouse—and how to choose between them.
- 1.3Workspace Security and Governance
Understand Fabric workspace roles (Admin/Member/Contributor/Viewer), item/row-level access control, sensitivity labels and governance with Purview, and deployment pipelines. Operate the analytics platform securely.
2Ingest and Transform Data
- 2.1Data Ingestion (Pipelines, Dataflows, Copy)
Understand ways to ingest data into Fabric—data pipelines (orchestration), Dataflows Gen2 (no-code transform with Power Query), the Copy activity, and shortcuts—and when to use each.
- 2.2Data Transformation (Spark, Notebooks, T-SQL)
Understand transformation in Fabric—Spark notebooks (PySpark/Spark SQL), Dataflows Gen2, T-SQL (Warehouse)—and the medallion architecture (bronze/silver/gold) for staged refinement.
3Monitor and Optimize an Analytics Solution
- 3.1Monitoring and Error Handling
Understand tracking runs via the Fabric Monitoring hub, error handling and retries for pipelines/notebooks, and capacity monitoring with the Capacity Metrics app. Find issues early and operate stably.
- 3.2Performance Optimization
Understand Fabric performance optimization: Delta V-Order and OPTIMIZE (file compaction), Spark configuration, Warehouse statistics, and Power BI Direct Lake.