Answer: A denormalized model that reduces the need for joins during analytical queries.

In a lakehouse environment, a denormalized model is the most efficient choice for supporting both analytical queries and transactional updates. This model combines tables and duplicates data to minimize the necessity for joins during analytical queries, thereby enhancing query performance. It also facilitates quicker transactional updates by reducing the number of tables involved in updates. While normalization is crucial for data integrity, a fully normalized model may not be as efficient in a lakehouse setting with complex data relationships. A snowflake schema offers a balance between normalization and query performance but may not match the efficiency of a denormalized model for both query and update operations. A flat table structure, although beneficial for fast reads, may not be as effective for transactional updates or complex analytical queries. Thus, the denormalized model provides the best compromise between performance, efficiency, and flexibility in a lakehouse environment.

Author: LeetQuiz Editorial Team