When multiple teams perform selective point-lookups on different columns of the same large table, traditional clustering is not effective because a table can have only one clustering key. Creating a composite clustering key across many columns often leads to poor clustering depth and limited pruning benefits.
The Search Optimization Service (SOS) is specifically designed for this scenario (Answer C). It enables fast point-lookups across multiple columns without requiring table reclustering. SOS maintains additional search access paths that accelerate highly selective predicates and is ideal when queries vary across many lookup columns.
Materialized views introduce additional storage, maintenance overhead, and operational complexity, and Snowflake does not automatically replace base tables with materialized views. This question tests an architect' s ability to choose the right optimization technique for multi-access-path workloads, a core SnowPro Architect competency.
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