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Databricks Databricks-Certified-Data-Engineer-Associate日本語 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Databricks Intelligence Platform10%- Platform architecture and core concepts
  • 1. Workspace navigation and management
  • 2. Compute options: clusters, SQL warehouses, serverless
  • 3. Data layout and optimization: partitioning, file sizing, caching
Topic 2: Development and Ingestion30%- Notebook development fundamentals
  • 1. Data exploration and validation
  • 2. Using PySpark and Spark SQL
- Data ingestion patterns and methods
  • 1. Connecting to external data sources
  • 2. Delta Lake basics and usage
  • 3. Batch and streaming ingestion
Topic 3: Data Governance & Quality11%- Unity Catalog implementation
  • 1. Permissions and access control
  • 2. Data governance model
- Data quality and reliability
  • 1. Schema enforcement and evolution
  • 2. Data validation and quality checks
Topic 4: Productionizing Data Pipelines18%- Monitoring and troubleshooting
  • 1. Logging and error handling
  • 2. Pipeline reliability and recovery
- Deployment and CI/CD
  • 1. Version control integration
  • 2. Databricks Asset Bundles
- Workflow orchestration
  • 1. Scheduling, triggers, and dependencies
  • 2. Lakeflow Jobs creation and management
Topic 5: Data Processing & Transformations31%- Query optimization and performance
  • 1. Optimization strategies
  • 2. Understanding query plans
- Data transformation techniques
  • 1. Complex data processing logic
  • 2. DataFrame operations and transformations
  • 3. Aggregations, joins, and window functions

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