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Snowflake SnowPro Core SnowPro Core Dumps in PDF

Free Snowflake SnowPro Core Real Questions (page: 6)

SnowPro Core PDF — 1300 Questions

Increasing the maximum number of clusters in a Multi-Cluster Warehouse is an example of:

  1. Scaling rhythmically
  2. Scaling max
  3. Scaling out
  4. Scaling up

Answer(s): C



Which statement best describes Snowflake tables?

  1. Snowflake tables are logical representations of underlying physical data
  2. Snowflake tables are the physical instantiation of data loaded into Snowflake
  3. Snowflake tables require that clustering keys be defined to perform optimally
  4. Snowflake tables are owned by a user

Answer(s): A


Reference:

https://docs.snowflake.com/en/user-guide/tables-micro-partitions.html



Which item in the Data Warehouse migration process does not apply in Snowflake?

  1. Migrate Users
  2. Migrate Schemas
  3. Migrate Indexes
  4. Build the Data Pipeline

Answer(s): C



Snowflake provides two mechanisms to reduce data storage costs for short-lived tables. These mechanisms are: (Choose two.)

  1. Temporary Tables
  2. Transient Tables
  3. Provisional Tables
  4. Permanent Tables

Answer(s): A,B


Reference:

https://docs.snowflake.com/en/user-guide/tables-storage-considerations.html



What is the maximum compressed row size in Snowflake?

  1. 8KB
  2. 16MB
  3. 50MB
  4. 4000GB

Answer(s): B



Which of the following are main sections of the top navigation of the Snowflake Web Interface (UI)? (Choose three.)

  1. Databases
  2. Tables
  3. Warehouses
  4. Worksheets

Answer(s): A,C,D


Reference:

https://docs.snowflake.com/en/user-guide/snowflake-manager.html



What is the recommended Snowflake data type to store semi-structured data like JSON?

  1. VARCHAR
  2. RAW
  3. LOB
  4. VARIANT

Answer(s): D


Reference:

https://docs.snowflake.com/en/sql-reference/data-types-semistructured.html



Which of the following statements are true of Snowflake releases: (Choose two.)

  1. They happen approximately weekly
  2. They roll up and release approximately monthly, but customers can request early release application
  3. During a release, new customer requests/queries/connections transparently move over to the newer version
  4. A customer is assigned a 30 minute window (that can be moved anytime within a week) during which the system will be unavailable and customer is upgraded

Answer(s): A,C



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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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