DEA-C02 Storage and Data Protection Practice Question
A data engineer is auditing storage consumption in a Snowflake account. A large permanent table named SALES_FACT has DATA_RETENTION_TIME_IN_DAYS set to 60. Over the past month, ETL jobs have performed several full-table UPDATE operations that rewrote most micro-partitions. The engineer notices that the table's Time Travel storage has grown significantly even though the visible row count is unchanged. What is the most likely cause of the increased Time Travel storage?
⚠ Common exam trap
The trap here is assuming that unchanged row counts imply unchanged storage, when in fact Time Travel storage is driven by the volume of historical micro-partition versions retained, not by the current row count.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Time Travel storage grows because each UPDATE creates new micro-partitions while prior versions are retained for the 60-day retention window.
Time Travel storage reflects historical micro-partition versions retained for the configured window. Each UPDATE that rewrites micro-partitions creates new versions, and the prior versions are stored for 60 days. Repeated full-table updates therefore accumulate substantial historical data, increasing Time Travel storage even when the visible row count is stable.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Time Travel storage grows because the 60-day retention forces Snowflake to store a full compressed copy of the table in Fail-safe.
Why it's wrong here
Fail-safe is a separate storage layer that begins after the Time Travel window expires, and it is not driven by the retention setting itself. Fail-safe storage is not what appears in the Time Travel storage metric. The growth described here comes from retained historical micro-partition versions during the active Time Travel window.
- ✓
Time Travel storage grows because each UPDATE creates new micro-partitions while prior versions are retained for the 60-day retention window.
Why this is correct
When UPDATE operations rewrite micro-partitions, Snowflake writes new versions and retains the prior versions for the duration of the Time Travel retention period. With a 60-day window and repeated full-table updates, many historical versions accumulate, driving up Time Travel storage even though the current row count is unchanged.
- ✗
Time Travel storage grows because Snowflake copies the entire table into a separate Time Travel schema on each UPDATE.
Why it's wrong here
Snowflake does not copy entire tables into a separate schema for Time Travel. Instead, historical versions are maintained as references to prior micro-partitions. The growth seen here is caused by the accumulation of those prior versions from the UPDATE operations, not by any schema-level duplication mechanism.
- ✗
Time Travel storage grows because the account has exceeded its storage quota, causing Snowflake to duplicate micro-partitions as a redundancy measure.
Why it's wrong here
Exceeding a storage quota does not cause Snowflake to duplicate micro-partitions. Quota enforcement affects the ability to perform write operations, not the internal storage layout. The growth in Time Travel storage is attributable to retained historical versions from UPDATE operations, not to any quota-driven duplication behavior.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Snowflake exam blueprint
This DEA-C02 practice question is part of Courseiva's free Snowflake certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C02 exam.