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Databricks Certified Professional Data Engineer : Databricks-Certified-Professional-Data-Engineer Exam

Databricks-Certified-Professional-Data-Engineer actual test
  • Exam Code: Databricks-Certified-Professional-Data-Engineer
  • Exam Name: Databricks Certified Professional Data Engineer Exam
  • Updated: May 30, 2026
  • Q & A: 217 Questions and Answers
  • PDF Demo
  • PC Test Engine
  • Online Test Engine
  • Total Price: $59.99  

About Databricks Certified Professional Data Engineer : Databricks-Certified-Professional-Data-Engineer Exam

Databricks Databricks-Certified-Professional-Data-Engineer Exam Syllabus Topics:

TopicDetails
Topic 1
  • Monitoring & Logging: This topic includes understanding the Spark UI, inspecting event timelines and metrics, drawing conclusions from various UIs, designing systems to control cost and latency SLAs for production streaming jobs, and deploying and monitoring both streaming and batch jobs.
Topic 2
  • Security & Governance: It discusses creating Dynamic views to accomplishing data masking and using dynamic views to control access to rows and columns.
Topic 3
  • Data Processing: The topic covers understanding partition hints, partitioning data effectively, controlling part-file sizes, updating records, leveraging Structured Streaming and Delta Lake, implementing stream-static joins and deduplication. Additionally, it delves into utilizing Change Data Capture and addressing performance issues related to small files.
Topic 4
  • Data Modeling: It focuses on understanding the objectives of data transformations, using Change Data Feed, applying Delta Lake cloning, designing multiplex bronze tables. Lastly it discusses implementing incremental processing and data quality enforcement, implementing lookup tables, and implementing Slowly Changing Dimension tables, and implementing SCD Type 0, 1, and 2 tables.
Topic 5
  • Databricks Tooling: The Databricks Tooling topic encompasses the various features and functionalities of Delta Lake. This includes understanding the transaction log, Optimistic Concurrency Control, Delta clone, indexing optimizations, and strategies for partitioning data for optimal performance in the Databricks SQL service.

Reference: https://www.databricks.com/learn/certification/data-engineer-professional

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