Which storage mode should dimension tables use to maximize caching and performance for filtering?

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Multiple Choice

Which storage mode should dimension tables use to maximize caching and performance for filtering?

Explanation:
The idea being tested is how storage mode affects in-memory caching and query performance for filtering. Filtering relies on quickly returning results, which is fastest when data is readily available in memory. DirectQuery keeps data in the source and doesn’t cache results, so filtering performance depends on the source itself and can be slower. Import loads the entire table into memory, giving the fastest, most responsive filtering, but it doesn’t offer real-time data freshness without refresh. Dual combines those advantages by maintaining a cached, in-memory copy for fast filtering while still allowing queries to leverage the source as needed. This provides the best balance for dimension tables used in filtering, delivering quick response times without sacrificing (where appropriate) access to the underlying data.

The idea being tested is how storage mode affects in-memory caching and query performance for filtering. Filtering relies on quickly returning results, which is fastest when data is readily available in memory. DirectQuery keeps data in the source and doesn’t cache results, so filtering performance depends on the source itself and can be slower. Import loads the entire table into memory, giving the fastest, most responsive filtering, but it doesn’t offer real-time data freshness without refresh. Dual combines those advantages by maintaining a cached, in-memory copy for fast filtering while still allowing queries to leverage the source as needed. This provides the best balance for dimension tables used in filtering, delivering quick response times without sacrificing (where appropriate) access to the underlying data.

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