Validates advanced skills in building, optimising, and maintaining production-grade data engineering solutions on the Databricks Data Intelligence Platform. Covers Delta Lake, Unity Catalog, Auto Loader, Lakeflow Spark Declarative Pipelines, Databricks Compute (including serverless), Lakeflow Jobs, and the Medallion Architecture. Assesses the ability to design secure, reliable, and cost-effective ETL pipelines, process complex data using Python and SQL, and apply best practices in schema management, observability, governance, and performance optimization. Also covers streaming workloads, workflow orchestration, DevOps and CI/CD, and deploying with the Databricks CLI, REST API, and Asset Bundles.
DEP Set 1
50 questions
DEP Set 2
50 questions
DEP Set 3
50 questions
DEP Set 4
50 questions
filter() transformation in PySpark return?sales at version 5?
SELECT customer_id, order_date, amount,
ROW_NUMBER() OVER (PARTITION BY customer_id ORDER BY order_date DESC) AS rn
FROM orders
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