How does Snowflake's support for materialized views contribute to query optimization and data analysis?

Question

Options

• AMaterialized views improve query performance by pre-computing results
• BMaterialized views restrict data access across warehouses
• CMaterialized views increase data storage requirements only
• DMaterialized views limit query optimization possibilities

• A
  88% (22)
• C
  4% (1)
• D
  8% (2)

Explanation

Materialized views pre-compute and store query results, so subsequent queries read from the cached result set rather than re-executing expensive joins, aggregations, or filters - directly boosting query performance and enabling faster data analysis. Option B is wrong because materialized views have no role in restricting cross-warehouse data access; that's handled by Snowflake's RBAC and account policies. Option C is a half-truth used as a trap: while materialized views do consume storage, framing that as their only contribution ignores their primary purpose and benefit. Option D is the opposite of reality - materialized views expand optimization possibilities by giving the query optimizer a pre-aggregated source to choose from.

Memory tip: Think of a materialized view as a "saved answer sheet" - the hard work is done once and reused many times, which is always a performance gain, never a restriction.

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