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

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

Topic	Details
Topic 1	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.
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	Testing & Deployment: It discusses adapting notebook dependencies to use Python file dependencies, leveraging Wheels for imports, repairing and rerunning failed jobs, creating jobs based on common use cases, designing systems to control cost and latency SLAs, configuring the Databricks CLI, and using the REST API to clone a job, trigger a run, and export the run output.
Topic 4	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 5	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.

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

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