Databricks Data Engineer Professional Question 131
Select 3While promoting data from the bronze to the silver layer in a Databricks Lakehouse architecture, what is the primary objective of performing data transformations?
- A
Filter out corrupt or incomplete records to ensure data quality.
- B
Enrich the data by joining it with reference datasets for additional context.
- C
Optimize the data for performance by reformatting it into a columnar storage format like Parquet.
- D
Aggregate the data to generate final business metrics for reporting purposes.
- E
Deduplicate records to remove redundancies and ensure data integrity.
Show answer and explanation
Correct answers: A, B, E
Explanation
The silver layer in the Databricks Lakehouse paradigm focuses on cleaning, enriching, and standardizing raw data from the bronze layer. This stage involves removing corrupt or incomplete records, enriching the data with relevant information, and ensuring data integrity by deduplicating records. While optimizing for performance and aggregating for final metrics are important, they are typically performed in the gold layer, which is tailored for analytics and reporting purposes.
- A. Correct.
Filtering out corrupt or incomplete records is a key step in promoting data from bronze to silver, as it ensures only high-quality data is processed further.
- B. Correct.
Enriching the data by adding context from reference datasets is a common transformation during the silver stage to make the data more meaningful.
- C. Incorrect.
Optimizing data for performance (e.g., reformatting into columnar formats) is typically a concern in the gold layer or for storage efficiency, not a primary objective of the silver layer.
- D. Incorrect.
Aggregating data for final business metrics is usually performed in the gold layer, not the silver layer, as silver focuses on clean and enriched data.
- E. Correct.
Removing duplicate records is critical for ensuring data integrity and is a common transformation in the silver layer.