Databricks Data Engineer Associate Question 15
Select 3A data engineering team is migrating their data storage from a traditional data lake to a data lakehouse architecture. Which of the following improvements in data quality can the team expect when using the data lakehouse?
- A
Support for enforcing schema validation to prevent ingestion of corrupt data
- B
Native support for ACID transactions to maintain consistency during concurrent writes
- C
Reduced storage costs due to the removal of redundant data
- D
Ability to implement fine-grained data governance and access controls
- E
Automated data deduplication without requiring custom scripts
Show answer and explanation
Correct answers: A, B, D
Explanation
The data lakehouse improves data quality over traditional data lakes by introducing schema enforcement, ACID transactions, and advanced governance capabilities. These features ensure that the data stored is accurate, consistent, and secure while addressing limitations of traditional data lakes. However, reduced storage costs and automated deduplication are not directly related to the improvement of data quality in a lakehouse.
- A. Correct.
Schema validation is a key feature of a data lakehouse, allowing the enforcement of data quality rules during ingestion. This prevents corrupt or invalid data from being stored.
- B. Correct.
The data lakehouse provides native support for ACID transactions, ensuring data consistency and reliability during concurrent operations, which is not typically available in traditional data lakes.
- C. Incorrect.
While a data lakehouse can optimize storage through better file management, reduced storage costs are not a direct improvement in data quality. This is unrelated to the question.
- D. Correct.
Data lakehouse architectures allow for fine-grained governance, such as row-level and column-level access controls, ensuring secure and compliant data usage. This directly improves data quality by ensuring only appropriate data is accessible.
- E. Incorrect.
Automated data deduplication is not a standard feature of a data lakehouse. Deduplication typically requires additional processing or tools, making this option incorrect.