Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version) : Databricks-Certified-Professional-Data-Engineer Korean exam

Databricks-Certified-Professional-Data-Engineer Korean
  • Exam Code: Databricks-Certified-Professional-Data-Engineer-KR
  • Exam Name: Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version)
  • Updated: Jul 06, 2026
  • Q & A: 217 Questions and Answers

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

TopicDetails
Topic 1
  • Security & Governance: It discusses creating Dynamic views to accomplishing data masking and using dynamic views to control access to rows and columns.
Topic 2
  • 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 3
  • 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 4
  • 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 5
  • 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.

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

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