Databricks Certified Data Engineer - Associate

Explanation

The correct answer is A. Avoiding vendor lock-in.

Why this is correct:

1. Open Source Foundation: Databricks Lakehouse Architecture is built on open source technologies like Apache Spark, Delta Lake, and MLflow. By embracing open standards, organizations avoid being locked into proprietary vendor-specific solutions.

2. Portability: Open source technologies provide portability across different cloud providers and on-premises environments, reducing dependency on any single vendor.

3. Community-driven Innovation: Open source projects benefit from community contributions and transparent development, ensuring long-term sustainability and avoiding proprietary limitations.

Why other options are incorrect:

• B. Simplified governance: While Databricks provides governance features, this is not the primary benefit of embracing open source technologies. Governance capabilities come from Databricks Unity Catalog and other proprietary features.

• C. Ability to scale workloads: Scalability is a feature of Databricks' architecture, but it's not specifically tied to open source technologies. Databricks provides managed Spark services that scale, but this benefit exists regardless of open source adoption.

• D. Cloud-specific integrations: This is actually the opposite of open source benefits. Open source technologies aim to be cloud-agnostic, while cloud-specific integrations would create vendor lock-in.

Key Takeaway:

Embracing open source technologies in the Lakehouse Architecture allows organizations to maintain flexibility, avoid proprietary lock-in, and leverage community-driven innovation while still benefiting from Databricks' managed services and enterprise features.