Databricks Certified Data Engineer - Associate

Explanation

Correct Answer: B

A data lakehouse's support for ACID-compliant transactions is the feature that directly results in improved data quality over a traditional data lake. Here's why:

Key Differences:

1. Traditional Data Lakes: Typically lack ACID (Atomicity, Consistency, Isolation, Durability) guarantees, which can lead to data quality issues such as:

   • Inconsistent reads during concurrent writes
   • Partial updates that can corrupt data
   • No rollback capabilities for failed operations
   • Difficulty maintaining data integrity

2. Data Lakehouse with ACID Compliance:

   • Atomicity: Ensures all operations in a transaction complete successfully or none do, preventing partial updates
   • Consistency: Maintains data integrity constraints throughout transactions
   • Isolation: Prevents concurrent transactions from interfering with each other
   • Durability: Ensures committed transactions persist even in case of system failures

Why Other Options Are Incorrect:

• A: While data lakehouses do handle both structured and unstructured data, this doesn't inherently improve data quality
• C: SQL query capability is about accessibility, not data quality
• D: Open formats (like Parquet, Delta Lake) enable interoperability but don't guarantee data quality
• E: ML/AI support is about workload capabilities, not data quality improvement

Real-World Impact:

ACID compliance in a data lakehouse architecture enables:

• Reliable data pipelines with rollback capabilities
• Consistent data views for all users
• Data quality enforcement through transactional guarantees
• Reduced data corruption and integrity issues

This feature is particularly important in production environments where data quality, consistency, and reliability are critical requirements.