A data engineer wants to reduce costs and optimize cloud spending. The data engineer has decided to use Databricks Serverless for lowering cloud costs while maintaining existing SLAs.
What is the first step in migrating to Databricks Serverless?

• A. A frequently running and efficient Python-based data transformation pipeline compatible with the latest Databricks runtime and Unity Catalog
• B. Legacy Ingestion pipelines that include ingestion from sources API's, files, JDBC/ODBC connections
• C. A frequently running and efficient Scala-based data transformation pipeline compatible with the latest Databricks runtime and Unity Catalog
• D. Low frequency BI Dashboarding and Adhoc SQL Analytics

A data engineer has left the organization. The data team needs to transfer ownership of the data engineer's Delta tables to a new data engineer. The new data engineer is the lead engineer on the data team.
Assuming the original data engineer no longer has access, which of the following individuals must be the one to transfer ownership of the Delta tables in Data Explorer?

• A. This transfer is not possible
• B. Original data engineer
• C. Databricks account representative
• D. New lead data engineer
• E. Workspace administrator

A data analyst has created a Delta table sales that is used by the entire data analysis team. They want help from the data engineering team to implement a series of tests to ensure the data is clean. However, the data engineering team uses Python for its tests rather than SQL.
Which of the following commands could the data engineering team use to access sales in PySpark?

• A. SELECT * FROM sales
• B. spark.sql("sales")
• C. There is no way to share data between PySpark and SQL.
• D. spark.table("sales")
• E. spark.delta.table("sales")

A data engineering team ingests customer transaction data from three enterprise sources (SQL database, S3, and Kafka stream) into Unity Catalog tables. The data must maintain lineage and support compliance audits requiring historical snapshots. Which Lakeflow Connect configuration satisfies both the governance and audit requirements?

• A. Separate connectors with full-load sync only, archival of historical data, and external tables for audit queries.
• B. Single Lakeflow connector with all three sources, direct Delta writes, and disabled table versioning to reduce storage costs.
• C. Separate connectors per source with CDC, individual Unity Catalog schemas per source, and table versioning enabled for audit compliance.
• D. Single connector with batch scheduling, shared Unity Catalog schema, and incremental snapshots stored externally.