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When designing a data model for time-series data in a lakehouse, which approach is most effective for optimizing query performance for time-based aggregations?
A
Store raw event data and use views to dynamically aggregate data on the-fly.
B
Use a flat wide table structure that pre-aggregates data at daily intervals.
C
Implement a star schema with a time dimension table that includes various time hierarchies.
D
Normalize the data into multiple dimension tables related to time, events, and entities.
