Databricks Certified Data Engineer Associate Exam covers a wide range of topics, including data ingestion, data transformation, data storage, data processing, and data analysis. It is designed to test the candidate's ability to work with a variety of data sources and formats, including structured, semi-structured, and unstructured data. It also tests the candidate's knowledge of data engineering best practices, such as data quality, data governance, and data security.
Reference: https://www.databricks.com/learn/certification/data-engineer-associate
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Databricks Databricks-Certified-Data-Engineer-Associate Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Data Governance and Quality | - Data access control and governance - Unity Catalog basics - Data quality concepts and management |
| Data Processing and Transformations | - Delta Lake fundamentals (tables, transactions, optimization) - PySpark DataFrame transformations - User-defined functions (UDFs) - Apache Spark SQL operations (joins, aggregations, filtering) |
| Data Ingestion and ELT Development | - ETL patterns and transformations - Handling structured and semi-structured data - Data ingestion using Spark SQL and PySpark |
| Productionizing Data Pipelines | - Databricks Workflows / Jobs orchestration - Pipeline deployment and operationalization - Scheduling and monitoring jobs |
| Databricks Lakehouse Platform Fundamentals | - Workspace, architecture, and core platform concepts - Clusters, notebooks, and basic Databricks environment usage |
