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Answer: A job that enriches data by parsing its timestamps into a human-readable format
## Explanation In the Databricks Lakehouse architecture, the **Bronze table** is the first layer where raw data is ingested and stored in its original format. The Bronze layer typically contains: - Raw, unprocessed data - Data in its original format (JSON, CSV, etc.) - Data that may need cleaning, transformation, or enrichment Looking at the options: - **Option A**: Aggregates cleaned data - This would use Silver or Gold tables as source, not Bronze - **Option B**: Queries aggregated data - This would use Gold tables for reporting/dashboards - **Option C**: Ingests raw data - This is the process that CREATES Bronze tables, not uses them as source - **Option D**: Develops feature sets - This typically uses Silver tables with cleaned, structured data - **Option E**: Enriches data by parsing timestamps - This is exactly the type of transformation that would use Bronze tables as source, taking raw data and performing initial data quality/enrichment operations Therefore, **Option E** is correct because parsing timestamps from raw data into human-readable format is a typical data enrichment operation that would use Bronze tables as the source.
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Question 29 Which of the following data workloads will utilize a Bronze table as its source?
A
A job that aggregates cleaned data to create standard summary statistics
B
A job that queries aggregated data to publish key insights into a dashboard
C
A job that ingests raw data from a streaming source into the Lakehouse
D
A job that develops a feature set for a machine learning application
E
A job that enriches data by parsing its timestamps into a human-readable format