SnowPro Core Certification Exam Questions and Answers
Question 9
When a Snowflake user loads CSV data from a stage, which copy into
command guideline should they follow?
Options:
A.
The CSV field delimiter must be a comma character (*,"),
B.
The number of columns in each row should be consistent.
C.
The data file in the stage must be in a compressed format.
D.
The data file must have the same number of columns as the target table.
Answer:
B
Explanation:
Explanation:
When using the COPY INTO <table> command to load CSV data from a stage into a Snowflake table, one of the crucial guidelines to follow is that the number of columns in each row within the CSV file should be consistent. This ensures data integrity and allows for a smooth data loading process, as Snowflake expects each row in the CSV file to map directly to a row in the target table based on the number of columns. If there's a mismatch in the number of columns between any row in the file and the target table, Snowflake might return an error or produce unexpected results during the load operation.
It's important to note that while the CSV field delimiter can be specified to something other than a comma, ensuring the consistency in the number of columns across all rows is fundamental to successfully loading data.
References:
Snowflake Documentation on Loading Data: Loading CSV Data
Question 10
Which Snowflake feature records changes mace to a table so actions can be taken using that change data capture?
Options:
A.
Materialized View
B.
Pipe
C.
Stream
D.
Task
Answer:
C
Explanation:
Explanation:
Snowflake's Streams feature is specifically designed for change data capture (CDC). A stream records insert, update, and delete operations performed on a table, and allows users to query these changes. This enables actions to be taken on the changed data, facilitating processes like incremental data loads and real-time analytics. Streams provide a powerful mechanism for applications to respond to data changes in Snowflake tables efficiently.References: Snowflake Documentation on Streams
Question 11
What information is stored in the ACCESS_HlSTORY view?
Options:
A.
History of the files that have been loaded into Snowflake
B.
Names and owners of the roles that are currently enabled in the session
C.
Query details such as the objects included and the user who executed the query
D.
Details around the privileges that have been granted for all objects in an account
Answer:
D
Explanation:
Explanation:
Details around the privileges that have been granted for all objects in an account. The ACCESS_HISTORY view in Snowflake provides a comprehensive log of access control changes, including grants and revocations of privileges on all securable objects within the account. This information is crucial for auditing and monitoring the security posture of your Snowflake environment.
Here's how to understand and use the ACCESS_HISTORY view:
Purpose of ACCESS_HISTORY View: It is designed to track changes in access controls, such as when a user or role is granted or revoked privileges on various Snowflake objects. This includes tables, schemas, databases, and more.
Querying ACCESS_HISTORY: To access this view, you can use the following SQL query pattern:
SELECT * FROM SNOWFLAKE.ACCOUNT_USAGE.ACCESS_HISTORY WHERE EVENT_TYPE = 'GRANT' OR EVENT_TYPE = 'REVOKE';
Interpreting the Results: The results from the ACCESS_HISTORY view include the object type, the specific privilege granted or revoked, the grantee (who received or lost the privilege), and the timestamp of the event. This data is invaluable for audits and compliance checks.
Reference: [Reference: For detailed information on the ACCESS_HISTORY view and how to interpret its data, please visit the official Snowflake documentation: https://docs.snowflake.com/en/sql-reference/account-usage/access_history.html, , ]
Question 12
The following settings are configured:
For how many days will the data be retained at the object level?
Options:
A.
2
B.
3
C.
5
D.
7
Answer:
A
Explanation:
Explanation:
The settings shown in the image indicate that the data retention time in days is configured at two different levels: the account level and the object level. At the account level, the MIN_DATA_RETENTION_TIME_IN_DAYS is set to 5 days, and at the object level, the DATA_RETENTION_TIME_IN_DAYS is set to 2 days. Since the object level setting has a lower value, it takes precedence over the account level setting for the specific object. Therefore, the data will be retained for 2 days at the object level.References: Snowflake Documentation on Data Retention Policies
