Exam DP-750: Implementing Data Engineering Solutions Using Azure Databricks
Proctored certification exam in beta with Microsoft’s standard exam experience.
- Type
- Written
- Duration
- 100 min
Passing score: 700 Scaled score
Exam sections
Set up and configure an Azure Databricks environment
Covers selecting and configuring compute types like job compute and serverless, managing performance settings such as autoscaling and node counts, and organizing Unity Catalog objects including catalogs, schemas, and tables while setting access permissions and libraries.
Preparation tips
Focus on understanding the different compute types and their performance settings, as well as the hierarchical organization of Unity Catalog objects.
Secure and govern Unity Catalog objects
Focuses on securing Unity Catalog objects through privileges, row-level security, and column masks. It also includes governing objects by managing tags, ABAC policies, and data lineage tracking, alongside implementing secure Delta Sharing strategies and audit logging.
Preparation tips
Understand how to implement fine-grained access control and how to track data lineage and audit logs within the Unity Catalog framework.
Prepare and process data
Covers data ingestion via Lakeflow Connect and Spark Structured Streaming, data cleansing, and complex transformations. Includes designing partitioning schemes, liquid clustering, and enforcing data quality constraints while managing schema drift and data modeling.
Preparation tips
Practice various ingestion methods and transformation techniques, particularly focusing on Delta Lake features like liquid clustering and schema enforcement.
Deploy and maintain data pipelines and workloads
Focuses on designing and implementing pipelines with Lakeflow Jobs and Asset Bundles. Includes managing development lifecycles via Git, monitoring workloads for performance tuning, and troubleshooting Spark jobs while optimizing Delta tables.
Preparation tips
Gain hands-on experience with Lakeflow Jobs and development lifecycle tools like Databricks Asset Bundles and Git integration.
