Databricks Certified Data Engineer - Associate

Correct Answer: B

Explanation:

A data lakehouse improves data quality over traditional data lakes primarily through ACID-compliant transactions. Here's why:

1. ACID Transactions Ensure Data Consistency: ACID (Atomicity, Consistency, Isolation, Durability) properties guarantee that data operations are reliable and consistent. This prevents data corruption and ensures data integrity during concurrent read/write operations.

2. Traditional Data Lakes Lack ACID: Traditional data lakes typically don't support ACID transactions, which can lead to data quality issues like:

   • Partial writes during failures
   • Inconsistent reads during concurrent writes
   • Data corruption from concurrent modifications

3. Other Options Analysis:

   • A: Storage for structured/unstructured data is common to both data lakes and lakehouses
   • C: SQL query capability is useful but doesn't inherently improve data quality
   • D: Open formats enable interoperability but don't guarantee data quality
   • E: ML/AI support is a workload capability, not a data quality feature

4. Databricks Implementation: In Databricks Lakehouse Platform, Delta Lake provides ACID transactions through:

   • Transaction logs
   • Versioning
   • Schema enforcement
   • Data validation

This ACID compliance is a key differentiator that directly addresses data quality challenges in traditional data lakes.