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Given a lakehouse dataset with billions of rows, which data modeling technique would you use to minimize query latency for multi-dimensional queries across diverse query patterns?
A
Create multiple materialized views, each optimized for a specific query pattern.
B
Utilize a single, flat table structure with extensive indexing on all queryable dimensions.
C
Partition the data by the most frequently queried dimension and use Z-order clustering on secondary dimensions.
D
Apply graph-based data modeling within Delta tables to exploit natural clustering of multi-dimensional data.
