Databricks Lakehouse Platform Architecture, workspace, clusters, Unity Catalog, and Delta Lake
Domain Weight Databricks Lakehouse Platform accounts for 24% of the Databricks-DE-Associate exam.
Understand how the lakehouse combines data lake flexibility with warehouse reliability using Delta Lake and Unity Catalog governance.
Data Lakehouse Open formats (Parquet/Delta) on cloud storage + ACID transactions + schema enforcement + BI performance.
Delta Lake ACID on object storage, time travel, schema evolution, OPTIMIZE/VACUUM, Change Data Feed.
Workspace Components Notebooks — collaborative Spark/Python/SQL development Clusters — all-purpose (interactive) vs job clusters (automated, terminate after) SQL warehouses — serverless or classic compute for BI queries Unity Catalog — three-level namespace: catalog.schema.table DBFS — legacy file system abstraction; prefer cloud URIs with UC volumes Repos — Git integration for notebook and code version control Cluster Types Job clusters cost less for production pipelines — they start for the job and terminate after. All-purpose clusters stay running for development.
Exam Focus Areas Unity Catalog is the governance layer — permissions, lineage, audit across workspaces Delta Lake provides ACID — plain Parquet on S3/ADLS does not Serverless SQL warehouses reduce cluster management overhead Practice This Domain Test your understanding with free practice questions at /certifications/databricks/data-engineer-associate/practice — focus on: Data lakehouse concepts and architecture, Databricks workspace and notebooks, Databricks clusters and compute resources.
