Snowflake Certification Practice Test 2026 – All-in-One Resource to Ensure Your Exam Success!

When clustering keys are ordered improperly in Snowflake, it significantly impacts query performance negatively. Clustering in Snowflake is designed to optimize how data is stored and retrieved based on the clustering keys you define. If these keys are not ordered properly, it can lead to inefficient data layout within the underlying micro-partitions that Snowflake uses.

Improperly ordered clustering keys can cause more data to be scanned than necessary during query execution. Since clustering influences how data is partitioned and organized on disk, queries that rely on those keys can experience slower performance due to increased I/O operations and decreased filtering efficiency. Snowflake may not be able to skip over entire micro-partitions that do not need to be read, thus requiring more time and resources to complete queries.

While the other options may suggest concerns like data loss or increased storage requirements, they do not directly relate to the fundamental purpose of clustering, which is to enhance query performance. Therefore, the focus should be on how the ordering of clustering keys directly impacts the performance of queries executed against the data in your Snowflake environment.