Databricks Certified Data Engineer - Associate

The correct answer is E. Data lakehouse.

Explanation:

A data lakehouse is a modern data architecture that combines the best features of data lakes and data warehouses. It is specifically designed to address the limitations of siloed data architectures:

1. Data Lake: Primarily stores raw, unstructured data but lacks robust transaction support, data quality enforcement, and performance optimizations for analytics.
2. Data Warehouse: Optimized for structured data and analytics but struggles with unstructured data and can be expensive for large-scale data storage.
3. Siloed Architectures: Traditional approaches often create separate systems for different use cases (e.g., one system for data science, another for BI reporting), leading to data duplication, inconsistency, and complexity.

The data lakehouse architecture unifies these approaches by:

• Providing low-cost storage like data lakes
• Offering ACID transactions and data quality features like data warehouses
• Supporting both structured and unstructured data
• Enabling direct access for various workloads (BI, data science, ML) without data movement
• Simplifying the overall data architecture by eliminating the need for multiple specialized systems

Therefore, the data lakehouse is specifically designed to simplify and unify siloed data architectures, making it the correct choice among the options provided.