Which solution is most suitable for creating a data store that supports dataflows and ensures delta tables are V-order optimized automatically?

• A. Data Lake
• B. Data Mart
• C. Lakehouse
• D. Data Warehouse

Answer: (C)

The main idea here is unifying storage with automatic, intelligent optimization for modern analytics workflows. A Lakehouse combines the flexibility of a data lake with the transactional guarantees and performance features of a data warehouse. It supports dataflows as a way to ingest and transform data and stores data in Delta-like tables that stay optimized for fast queries through automatic layout improvements, such as V-order optimization, without manual tuning.

That combination is why Lakehouse is the best fit: it provides a single platform where dataflows can feed data into a unified store, and Delta tables are kept optimized automatically for efficient query performance.

A data lake alone lacks strong transactional guarantees and built-in, automatic optimization for Delta-style tables. A data warehouse offers fast, structured query performance but doesn’t provide the lake’s flexible storage and broad data types. A data mart is a focused, departmental slice of a data warehouse and doesn’t capture the broad, unified capabilities of a lakehouse.