You are designing a data model in a Databricks lakehouse to support multi-dimensional analytics for a retail company. How would you structure the data to optimize for query performance across numerous dimensions such as time, geography, product, and customer demographics?

Real Exam

Store all data in a single, flattened wide table to minimize join operations during query execution.

12.3%

Normalize the data into multiple related tables to reduce redundancy and save on storage costs.

3.1%

Implement a star schema design with dimension tables for time, geography, product, and customer demographics, centering around a sales fact table.

76.9%

Use a snowflake schema but avoid creating dimension tables for highly hierarchical dimensions like geography.

7.7%

Databricks Certified Data Engineer - Professional