Explanation:
Explanation:
In the Databricks Lakehouse architecture, data typically flows through three layers:
Gold tables contain aggregated, business-ready data that has been processed for specific use cases like reporting, analytics, and dashboards. Therefore:
Option D is correct because querying aggregated data designed to feed into a dashboard is exactly what Gold tables are designed for.
Option A (enriching data by parsing timestamps) is typically a Silver layer activity.
Option B (aggregating uncleaned data) would use Bronze or Silver as source, not Gold.
Option C (cleaning data by removing malformed records) is a Silver layer activity.
Option E (ingesting raw data from streaming sources) is a Bronze layer activity.
Gold tables represent the final, refined data layer optimized for business consumption, making them the appropriate source for dashboard queries and reporting workloads.
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Which of the following data workloads will utilize a Gold table as its source?
A
A job that enriches data by parsing its timestamps into a human-readable format
B
A job that aggregates uncleaned data to create standard summary statistics
C
A job that cleans data by removing malformed records
D
A job that queries aggregated data designed to feed into a dashboard
E
A job that ingests raw data from a streaming source into the Lakehouse