Databricks Data Engineer Associate Question 11
Select 3In the context of improving data quality, what advantages does a data lakehouse offer over a traditional data lake?
- A
Support for ACID transactions ensures consistency and reliability of data operations.
- B
Schema enforcement prevents ingestion of invalid data into tables.
- C
Data lakehouses eliminate the need for any ETL processes, ensuring faster data ingestion.
- D
Unified storage allows for seamless integration of structured, semi-structured, and unstructured data.
- E
Data lakehouses automatically clean and validate data without requiring any user intervention.
Show answer and explanation
Correct answers: A, B, D
Explanation
Data lakehouses improve data quality over traditional data lakes by introducing features like ACID transactions, schema enforcement, and unified storage. These features enable consistent, validated, and integrated data management, which traditional data lakes often struggle to achieve without additional tooling or processes.
- A. Correct.
Support for ACID transactions ensures that operations like updates and deletes are reliable and data remains consistent, which is a major improvement over traditional data lakes that lack such capabilities.
- B. Correct.
Schema enforcement in data lakehouses ensures that only valid data conforming to a predefined schema is accepted, reducing the risk of data quality issues.
- C. Incorrect.
Data lakehouses still require ETL processes in many scenarios, although they simplify the architecture by combining storage and analytics. This option is incorrect as it misrepresents the purpose of a data lakehouse.
- D. Correct.
Unified storage allows data lakehouses to manage structured, semi-structured, and unstructured data in one platform, improving data integration and accessibility while maintaining quality.
- E. Incorrect.
While data lakehouses provide tools for data validation and quality checks, they require user-defined logic or configurations to clean and validate data. This option is incorrect as it overstates the automation capabilities of data lakehouses.