A Snowflake administrator is tasked with managing storage costs. They notice that several large tables are rarely queried. Which of the following strategies are MOST effective for reducing storage cos

Question

Options

• ADropping the tables and recreating them when needed from source data.
• BCloning the tables to a cheaper storage solution outside of Snowflake.
• CSetting a data retention period for the tables using Time Travel and Fail-safe.
• DPurging the tables completely to reclaim storage space.
• EUsing Snowflake's data compression, which is automatically enabled and optimizes storage

• A
  2% (1)
• B
  20% (8)
• C
  68% (28)
• D
  10% (4)

Explanation

Reducing the Time Travel retention period on rarely-queried tables (option C) directly lowers storage costs because Snowflake charges for historical data snapshots - setting a shorter retention window (e.g., 0–1 day) means fewer snapshots are stored, while the table itself remains fully accessible. Snowflake's automatic columnar compression (option E) is always active and significantly reduces the physical storage footprint of large tables at no extra configuration cost, making it a passive but powerful cost-saver. Options A and D are wrong because they eliminate future access entirely (dropping or purging destroys the data or makes recreation complex and risky). Option B misrepresents how Snowflake cloning works - zero-copy clones remain inside Snowflake and don't reduce storage costs; exporting data externally introduces egress costs and removes native accessibility.

Memory tip: Think "Shrink the window, shrink the data" - shorten Time Travel to shrink historical snapshot storage (C), and trust Snowflake's built-in compression to shrink active data size (E). If an option destroys access or moves data out, it fails the "future access" requirement.

No community discussion yet for this question.