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Snowflake SnowPro Core SnowPro Core Dumps in PDF

Free Snowflake SnowPro Core Real Questions (page: 17)

SnowPro Core PDF — 1300 Questions

Which of the following accurately represents how a table fits into Snowflake's logical container hierarchy?

  1. Account -> Schema -> Database -> Table
  2. Account -> Database -> Schema -> Table
  3. Database -> Schema -> Table -> Account
  4. Database -> Table -> Schema -> Account

Answer(s): B


Reference:

https://docs.snowflake.com/en/sql-reference/ddl-database.html



True or False: All Snowflake table types include fail-safe storage.

  1. True
  2. False

Answer(s): B



What are two ways to create and manage Data Shares in Snowflake? (Choose two.)

  1. Via the Snowflake Web Interface (UI)
  2. Via the DATA_SHARE=TRUE parameter
  3. Via SQL commands
  4. Via Virtual Warehouses

Answer(s): A,C


Reference:

https://docs.snowflake.com/en/user-guide/data-sharing-provider.html



True or False: Fail-safe can be disabled within a Snowflake account.

  1. True
  2. False

Answer(s): B



True or False: It is possible for a user to run a query against the query result cache without requiring an active Warehouse.

  1. True
  2. False

Answer(s): A



True or False: When Snowflake is configured to use Single Sign-On (SSO), Snowflake receives the usernames and credentials from the SSO service and loads them into the customer's Snowflake account.

  1. True
  2. False

Answer(s): B


Reference:

https://docs.snowflake.com/en/user-guide/admin-security-fed-auth-configure-snowflake.html



Which of the following are best practices for loading data into Snowflake? (Choose three.)

  1. Aim to produce data files that are between 100 MB and 250 MB in size, compressed.
  2. Load data from files in a cloud storage service in a different region or cloud platform from the service or region containing the Snowflake account, to save on cost.
  3. Enclose fields that contain delimiter characters in single or double quotes.
  4. Split large files into a greater number of smaller files to distribute the load among the compute resources in an active warehouse.
  5. When planning which warehouse(s) to use for data loading, start with the largest warehouse possible.
  6. Partition the staged data into large folders with random paths, allowing Snowflake to determine the best way to load each file.

Answer(s): A,C,D



Which Snowflake feature is used for both querying and restoring data?

  1. Cluster keys
  2. Time Travel
  3. Fail-safe
  4. Cloning

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.

Pune, India
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.

Johannesburg, South Africa
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.

Chennai, India
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