Snowflake SnowPro Core SnowPro Core Dumps in PDF

Free Snowflake SnowPro Core Real Questions (page: 52)

When should a multi-cluster warehouse be used in auto-scaling mode?

  1. When it is unknown how much compute power is needed
  2. If the select statement contains a large number of temporary tables or Common Table Expressions (CTEs)
  3. If the runtime of the executed query is very slow
  4. When a large number of concurrent queries are run on the same warehouse

Answer(s): D



What happens when a cloned table is replicated to a secondary database? (Choose two.)

  1. A read-only copy of the cloned tables is stored.
  2. The replication will not be successful.
  3. The physical data is replicated.
  4. Additional costs for storage are charged to a secondary account.
  5. Metadata pointers to cloned tables are replicated.

Answer(s): C,D



Snowflake supports the use of external stages with which cloud platforms? (Choose three.)

  1. Amazon Web Services
  2. Docker
  3. IBM Cloud
  4. Microsoft Azure Cloud
  5. Google Cloud Platform
  6. Oracle Cloud

Answer(s): A,D,E



What is a limitation of a Materialized View?

  1. A Materialized View cannot support any aggregate functions
  2. A Materialized View can only reference up to two tables
  3. A Materialized View cannot be joined with other tables
  4. A Materialized View cannot be defined with a JOIN

Answer(s): D



In the Snowflake access control model, which entity owns an object by default?

  1. The user who created the object
  2. The SYSADMIN role
  3. Ownership depends on the type of object
  4. The role used to create the object

Answer(s): D



What is the minimum Snowflake edition required to use Dynamic Data Masking?

  1. Standard
  2. Enterprise
  3. Business Critical
  4. Virtual Private Snowflake (VPC)

Answer(s): B



Which services does the Snowflake Cloud Services layer manage? (Choose two.)

  1. Compute resources
  2. Query execution
  3. Authentication
  4. Data storage
  5. Metadata

Answer(s): C,E



A company needs to allow some users to see Personally Identifiable Information (PII) while limiting other users from seeing the full value of the PII.

Which Snowflake feature will support this?

  1. Row access policies
  2. Data masking policies
  3. Data encryption
  4. Role based access control

Answer(s): B



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A
AI Tutor Explanation
9/24/2026 11:16:10 AM

Question 5:
Correct answer: A — True
Snowflake supports bulk unloading with COPY INTO <location> using a SELECT statement as the source. This allows you to export either:

  • All or selected columns from a table
  • Filtered rows using WHERE
  • Transformed or joined data

Example:
sql 
COPY INTO @my_stage/export/ 
FROM ( 
  SELECT customer_id, order_date 
  FROM orders 
  WHERE order_date >= '2025-01-01' 
);

Snowflake writes the query results to files in the specified internal or external stage. The key distinction is that COPY INTO is used for bulk movement of data, while a regular SELECT only returns query results and does not unload them to staged files.

A
AI Tutor Explanation
9/3/2026 5:25:59 AM

Question 1:
Correct answer: B — Clustering keys
Snowflake automatically organizes table data into micro-partitions and uses natural clustering based on how data is loaded. However, for large tables where query performance depends on particular columns, you can define a clustering key.
A clustering key:

  • Specifies one or more columns or expressions Snowflake should use when organizing table data.
  • Helps Snowflake’s automatic reclustering keep related rows grouped together.
  • Can improve pruning for queries that frequently filter or join on those columns.

Why the others are incorrect:
  • Micro-partitions: Snowflake’s storage units; users do not directly define them as an override mechanism.
  • Key partitions: Not a Snowflake feature.
  • Clustered partitions: Not the name of the customer-defined mechanism.

The answer key’s B is correct.

A
AI Tutor Explanation
8/28/2026 11:39:56 AM

Question 17:
Correct answer: D — To accommodate a more complex workload.
Increasing a Virtual Warehouse from X-Small to Medium is vertical scaling. The larger warehouse provides more compute resources, which can improve performance for:

  • Complex queries
  • Large scans or joins
  • Resource-intensive transformations
  • Queries involving substantial processing

Why the others are less appropriate:
  • More users / more queries: This usually calls for multi-cluster warehouses, which add clusters to handle concurrency.
  • Fluctuations in workload: This is typically addressed with auto-suspend/auto-resume or multi-cluster scaling, rather than simply choosing a larger warehouse.

Thus, warehouse size primarily affects the compute power available to individual workloads.

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