When manipulating data in Snowflake, what distinguishes aggregate functions from analytic functions?

Question

Options

• AAggregate functions handle distinct value sets only
• BAggregate functions work on entire datasets
• CAnalytic functions operate on individual rows within a partition
• DAnalytic functions return single calculated values

• A
  7% (4)
• B
  5% (3)
• C
  86% (48)
• D
  2% (1)

Explanation

Analytic (window) functions operate on a set of rows related to the current row - defined by a PARTITION BY or ORDER BY clause - while still returning a value for each individual row, making option C correct. Aggregate functions (A, B, D confusion) collapse multiple rows into a single summary value per group, such as SUM() or COUNT() in a GROUP BY query - they reduce rows, they don't preserve them. Option A is wrong because aggregate functions work on any value set, not just distinct ones. Option B is misleading: aggregate functions work on groups within a dataset, not necessarily the entire dataset as one unit. Option D describes aggregate behavior, not analytic - analytic functions return one value per row, not one value overall.

Memory tip: Think of analytic functions as giving each row its own "window" to look through at neighboring rows - the row stays in the result, but it gains context from its peers. Aggregate functions collapse the crowd; analytic functions inform each member of it.

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