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Databricks Certified Professional Data Engineer certification exam is a rigorous and challenging exam that requires a deep understanding of data engineering concepts and the Databricks platform. Candidates must have a strong foundation in computer science and data engineering, as well as practical experience using the Databricks platform. Databricks-Certified-Professional-Data-Engineer-KR exam consists of multiple-choice questions and hands-on exercises that test a candidate's ability to design, build, and maintain data pipelines using the Databricks platform.
Reference: https://www.databricks.com/learn/certification/data-engineer-professional
Databricks Certified Professional Data Engineer certification exam is a challenging exam that requires candidates to have a deep understanding of Databricks technologies and data engineering concepts. Candidates must have experience working with Apache Spark, Delta Lake, SQL, and Python. They must also have experience working with cloud-based data platforms such as AWS, Azure, or Google Cloud Platform.
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| Section | Objectives |
|---|---|
| Topic 1: Data Modeling and Storage | - Delta Lake table design and optimization - Schema evolution and data partitioning strategies - Design scalable data lakehouse architectures |
| Topic 2: Production Pipelines and Orchestration | - Automate ETL pipelines and scheduling - Build and manage workflows using Databricks Jobs - Pipeline reliability and fault tolerance |
| Topic 3: Data Ingestion and Transformation | - Handle batch and streaming data pipelines - Ingest data using Apache Spark and Databricks - Transform and clean datasets using Spark SQL and DataFrame APIs |
| Topic 4: Security, Governance, Monitoring, and Optimization | - Monitor and optimize Spark workloads - Implement Unity Catalog governance and access control - Cost optimization and performance tuning |
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