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When designing a data model for multi-dimensional data analysis (e.g., OLAP cubes) in a lakehouse, which approach ensures optimal query performance across various aggregation queries?
A
Store raw event data in a flat structure, applying on-the-fly aggregation during each query.
B
Implement a snowflake schema, normalizing dimensions to reduce data redundancy and storage costs.
C
Pre-aggregate data into a set of materialized views covering common query patterns.
D
Utilize a star schema with fact tables and dimension tables, leveraging Delta Lake‘s performance features.
