Databricks Certified Data Engineer - Associate

Explanation

Correct Answer: B

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

Key Differences:

1. Traditional Data Lake:

   • Primarily designed for storing raw, unprocessed data
   • Lacks built-in transaction support
   • Data quality issues can arise from concurrent reads/writes
   • No guarantees of data consistency

2. Data Lakehouse:

   • ACID (Atomicity, Consistency, Isolation, Durability) compliance ensures:
     • Atomicity: Transactions are all-or-nothing operations
     • Consistency: Data remains in a valid state after transactions
     • Isolation: Concurrent transactions don't interfere with each other
     • Durability: Committed transactions persist even after system failures

Why ACID Transactions Improve Data Quality:

• Prevents data corruption from concurrent writes
• Ensures data consistency across multiple operations
• Provides reliable data updates without compromising existing data
• Enables reliable data pipelines with rollback capabilities
• Supports time travel and data versioning features

Analysis of Other Options:

• A: Storage solutions for structured/unstructured data - Both data lakes and lakehouses provide this, not a quality improvement
• C: SQL query support - While useful, doesn't inherently improve data quality
• D: Open format storage - Both support open formats, not a quality differentiator
• E: ML/AI workloads - Both can support these, not directly related to data quality

The ACID compliance in data lakehouses directly addresses the data quality challenges that plague traditional data lakes, making option B the correct answer.