Data Engineering Associate with Databricks Practice Exam

Disable ads (and more) with a membership for a one time $4.99 payment

Study for the Data Engineering Associate exam with Databricks. Use flashcards and multiple choice questions with hints and explanations. Prepare effectively and confidently for your certification exam!

Practice this question and more.

How can a data engineer ensure data integrity when using Delta Lake?

By utilizing table versioning
By implementing strict access controls
By overwriting existing data
By monitoring data ingestion speed

The correct answer is: By utilizing table versioning

Using table versioning in Delta Lake plays a crucial role in ensuring data integrity. Delta Lake maintains a transaction log, which allows for multiple versions of a table to be saved. Each time data is modified, a new version is created rather than overwriting the original data. This capability provides several benefits related to data integrity: 1. **Atomic Transactions**: Delta Lake supports ACID (Atomicity, Consistency, Isolation, Durability) transactions, ensuring that all operations on the data either complete successfully or leave the database in its previous state. This minimizes the risk of partial data writes, which could lead to data inconsistencies. 2. **Time Travel**: With versioning, a data engineer can retrieve previous versions of a dataset easily. This "time travel" capability allows for audits and quick recovery in case of data corruption or accidental deletions, thus preserving the integrity of the historical data. 3. **Schema Evolution**: Table versioning supports the management of schema changes over time, allowing tables to evolve without losing the integrity of existing data or needing manual interventions. These features combined significantly enhance the reliability and accuracy of the data stored in Delta Lake, making it a powerful tool for data engineers aiming to uphold data integrity in their data pipelines.