How does leveraging Time Travel feature in Snowflake aid in query optimization and historical data analysis?

Question

Options

• AOffers options to alter query execution plans
• BLimits query execution time
• CProvides real-time data updates
• DEnables querying of historical data versions

• A
  2% (1)
• B
  5% (2)
• C
  2% (1)
• D
  90% (37)

Explanation

Snowflake's Time Travel feature enables querying historical versions of data by specifying a past timestamp, statement ID, or offset - making D correct, as it directly allows analysis of data as it existed at a prior point in time. This is invaluable for auditing changes, recovering accidentally deleted/modified data, and comparing historical states without maintaining separate snapshot tables.

Why the distractors are wrong:

• A is wrong - Time Travel has nothing to do with altering query execution plans; that's the domain of query profiling and clustering keys.
• B is wrong - Time Travel does not impose or manage query execution time limits; those are controlled by resource monitors and warehouse sizing.
• C is wrong - Time Travel is the opposite of real-time; it looks backward in time, not forward to live updates.

Memory tip: Think of Time Travel like a DVR for your database - you can rewind and replay what your data looked like at any past moment, up to 90 days (Enterprise tier). The keyword is historical, not current or faster.

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