When a replication schedule is set, how does Snowflake manage refreshes for failover groups?
Correct Answer: B
The correct answer is B. Only one refresh will run at a time . Failover groups can be refreshed on a schedule to replicate supported account objects and database objects to target accounts. Snowflake does not run overlapping refresh operations for the same failover group. Why B is correct: If a scheduled refresh is still running, Snowflake does not start another concurrent refresh for the same failover group. Refresh operations are managed so that only one refresh runs at a time. Why the other options are incorrect: A). Multiple refreshes for the same failover group do not run concurrently. C). Refreshes still require the appropriate privileges and configured replication/failover group permissions. D). A delayed or long-running refresh does not mean the next refresh is automatically canceled in the way stated. The key behavior is that refreshes do not overlap. Official Snowflake documentation reference: Snowflake documentation for replication and failover groups explains that scheduled refreshes are managed by Snowflake and that refresh operations do not run concurrently for the same group. Reference: Snowflake Documentation - Replication and failover groups; Snowflake Documentation - Failover group refresh; SnowPro Core Study Guide - Snowflake Account and Resource Management.
Question 352
When is the VARIANT data type suitable when using semi-structured data? (Select TWO).
Correct Answer: B,D
Question 353
Taking which step will minimize the number of queries waiting to run on a virtual warehouse?
Correct Answer: D
The correct answer is D. Increase the value of the MAX_CLUSTER_COUNT . Queries wait in a queue when a warehouse does not have enough available compute capacity to handle the current concurrency. For a multi-cluster warehouse, increasing MAX_CLUSTER_COUNT allows Snowflake to start more clusters when concurrency increases. Why D is correct: Increasing MAX_CLUSTER_COUNT allows a multi-cluster warehouse in Auto-scale mode to add more clusters, up to the configured maximum. This helps reduce query queuing for concurrent workloads. Why the other options are incorrect: A). Increasing WAREHOUSE_SIZE gives each cluster more compute power, which can help individual queries run faster, but it is not the best direct solution for reducing queued concurrent queries. B). Increasing AUTO_SUSPEND keeps the warehouse running longer but does not increase concurrency capacity. C). WAIT_FOR_COMPLETION = FALSE is used with warehouse resize behavior and does not reduce query queuing. Official Snowflake documentation reference: Snowflake documentation explains that multi-cluster warehouses improve concurrency by starting additional clusters as query demand increases. The MAX_CLUSTER_COUNT property defines the maximum number of clusters that can run. Reference: Snowflake Documentation - Multi-cluster warehouses; Snowflake Documentation - Warehouse properties; SnowPro Core Study Guide - Snowflake Account and Resource Management. ==
Question 354
How does Snowflake Copilot interact with customer data?
Correct Answer: B
The correct answer is B. Copilot provides assistance when creating and interpreting queries . Snowflake Copilot is an AI-assisted feature that helps users work with Snowflake more efficiently. It can assist with writing SQL, understanding queries, and interpreting query-related information. Why B is correct: Copilot is designed to help users create, refine, and understand SQL queries using natural language assistance. Why the other options are incorrect: A). Query optimization is primarily handled by Snowflake's optimizer and performance features, not Copilot. C). Copilot does not automatically rewrite table schemas based on inferred data patterns. D). Copilot is not primarily a feature for executing stored procedures from prompts. Official Snowflake documentation reference: Snowflake documentation describes Snowflake Copilot as an AI assistant for helping users generate, understand, and work with SQL and Snowflake data workflows. Reference: Snowflake Documentation - Snowflake Copilot; Snowflake Cortex; SnowPro Core Study Guide - Snowflake Architecture. ==
Question 355
What does the NULL_IF parameter do when loading CSV data into Snowflake?
Correct Answer: B
NULL_IF identifies one or more source-file strings that Snowflake should interpret as SQL NULL while loading data. For example, a file format can define NULL_IF = ( ' NULL ' , ' NUL ' , ' \N ' , ' ' ). When Snowflake encounters any specified value in the CSV input, it loads a SQL NULL into the corresponding target column. The parameter does not remove rows or values from the dataset, convert binary content, or automatically replace NULL values with empty strings. Snowflake applies the conversion to every occurrence of a configured value, regardless of whether that value visually resembles text or a number. When unloading data, NULL_IF works in the opposite direction by converting SQL NULL values into the first specified output string, but this question specifically concerns loading CSV data.
