100% PASS 2025 ADA-C01: UNPARALLELED SNOWPRO ADVANCED ADMINISTRATOR VALID TEST VOUCHER

100% Pass 2025 ADA-C01: Unparalleled SnowPro Advanced Administrator Valid Test Voucher

100% Pass 2025 ADA-C01: Unparalleled SnowPro Advanced Administrator Valid Test Voucher

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Snowflake SnowPro Advanced Administrator Sample Questions (Q37-Q42):

NEW QUESTION # 37
MY_TABLE is a table that has not been updated or modified for several days. On 01 January 2021 at 07:01, a user executed a query to update this table. The query ID is
'8e5d0ca9-005e-44e6-b858-a8f5b37c5726'. It is now 07:30 on the same day.
Which queries will allow the user to view the historical data that was in the table before this query was executed? (Select THREE).

  • A. SELECT * FROM TIME_TRAVEL ('MY_TABLE', 2021-01-01 07:00:00);
  • B. SELECT * FROM my table WITH TIME_TRAVEL (OFFSET => -60*30);
  • C. SELECT * FROM my_table AT (TIMESTAMP => '2021-01-01 07:00:00' :: timestamp);
  • D. SELECT * FROM my_table AT (OFFSET => -60*30);
  • E. SELECT * FROM my_table BEFORE (STATEMENT => '8e5d0ca9-005e-44e6-b858-a8f5b37c5726');
  • F. SELECT * FROM my table PRIOR TO STATEMENT '8e5d0ca9-005e-44e6-b858-a8f5b37c5726';

Answer: C,E,F

Explanation:
Explanation
According to the AT | BEFORE documentation, the AT or BEFORE clause is used for Snowflake Time Travel, which allows you to query historical data from a table based on a specific point in the past. The clause can use one of the following parameters to pinpoint the exact historical data you wish to access:
*TIMESTAMP: Specifies an exact date and time to use for Time Travel.
*OFFSET: Specifies the difference in seconds from the current time to use for Time Travel.
*STATEMENT: Specifies the query ID of a statement to use as the reference point for Time Travel.
Therefore, the queries that will allow the user to view the historical data that was in the table before the query was executed are:
*B. SELECT * FROM my_table AT (TIMESTAMP => '2021-01-01 07:00:00' :: timestamp); This query uses the TIMESTAMP parameter to specify a point in time that is before the query execution time of 07:01.
*D. SELECT * FROM my table PRIOR TO STATEMENT '8e5d0ca9-005e-44e6-b858-a8f5b37c5726'; This query uses the PRIOR TO STATEMENT keyword and the STATEMENT parameter to specify a point in time that is immediately preceding the query execution time of 07:01.
*F. SELECT * FROM my_table BEFORE (STATEMENT => '8e5d0ca9-005e-44e6-b858-a8f5b37c5726'); This query uses the BEFORE keyword and the STATEMENT parameter to specify a point in time that is immediately preceding the query execution time of 07:01.
The other queries are incorrect because:
*A. SELECT * FROM my table WITH TIME_TRAVEL (OFFSET => -60*30); This query uses the OFFSET parameter to specify a point in time that is 30 minutes before the current time, which is 07:30. This is after the query execution time of 07:01, so it will not show the historical data before the query was executed.
*C. SELECT * FROM TIME_TRAVEL ('MY_TABLE', 2021-01-01 07:00:00); This query is not valid syntax for Time Travel. The TIME_TRAVEL function does not exist in Snowflake. The correct syntax is to use the AT or BEFORE clause after the table name in the FROM clause.
*E. SELECT * FROM my_table AT (OFFSET => -60*30); This query uses the AT keyword and the OFFSET parameter to specify a point in time that is 30 minutes before the current time, which is 07:30. This is equal to the query execution time of 07:01, so it will not show the historical data before the query was executed. The AT keyword specifies that the request is inclusive of any changes made by a statement or transaction with timestamp equal to the specified parameter. To exclude the changes made by the query, the BEFORE keyword should be used instead.


NEW QUESTION # 38
A Snowflake Administrator created a role ROLE_MANAGED_ACCESS and a schema SCHEMA_MANAGED_ACCESS as follows:
USE ROLE SECURITYADMIN;
CREATE ROLE ROLE_MANAGED_ACCESS;
GRANT ROLE ROLE_MANAGED_ACCESS TO ROLE SYSADMIN;
GRANT USAGE ON WAREHOUSE COMPUTE_WH TO ROLE ROLE_MANAGED_ACCESS;
GRANT ALL privileges ON DATABASE WORK TO ROLE ROLE_MANAGED_ACCESS;
USE ROLE ROLE_MANAGED_ACCESS;
CREATE SCHEMA SCHEMA_MANAGED_ACCESS WITH MANAGED ACCESS;
USE ROLE SECURITYADMIN;
GRANT SELECT, INSERT ON FUTURE TABLES IN SCHEMA SCHEMA MANAGED ACCESS to ROLE_MANAGED_ACCESS; The Administrator now wants to disable the managed access on the schema.
How can this be accomplished?

  • A. ALTER SCHEMA SCHEMA MANAGED ACCESS DISABLE MANAGED ACCESS;
  • B. REVOKE SELECT, INSERT ON FUTURE TABLES IN SCHEMA SCHEMA_MANAGED_ACCESS FROM ROLE_MANAGED_ACCESS; ALTER SCHEMA SCHEMA MANAGED ACCESS DISABLE MANAGED ACCESS;
  • C. USE ROLE ROLE MANAGED_ACCESS;
    DROP SCHEMA WORK. SCHEMA_MANAGED_ACCESS;
    CREATE SCHEMA SCHEMA_MANAGED_ACCESS;
    Then recreate all needed objects.
  • D. USE ROLE ROLE_MANAGED_ACCESS;
    DROP SCHEMA WORK. SCHEMA MANAGED_ACCESS;
    CREATE SCHEMA SCHEMA_MANAGED_ACCESS WITHOUT MANAGED ACCESS;
    Then recreate all needed objects.

Answer: A

Explanation:
Explanation
According to the Snowflake documentation1, you can change a managed access schema to a regular schema using the ALTER SCHEMA statement with the DISABLE MANAGED ACCESS keywords. This will disable the managed access feature on the schema and revert the access control to the default behavior. Option B is incorrect because dropping and recreating the schema will also delete all the objects and metadata in the schema, which is not necessary to disable the managed access. Option C is incorrect because revoking the privileges on the future tables from the role is not required to disable the managed access. Option D is incorrect because there is no WITHOUT MANAGED ACCESS option in the CREATE SCHEMA statement.


NEW QUESTION # 39
An Administrator receives data from a Snowflake partner. The partner is sharing a dataset that contains multiple secure views. The Administrator would like to configure the data so that only certain roles can see certain secure views.
How can this be accomplished?

  • A. Individually grant imported privileges onto the schema in the share.
  • B. Clone the data and insert it into a company-owned share and apply the desired RBAC on the new tables.
  • C. Create views over the incoming shared database and apply the desired RBAC onto these views.
  • D. Apply RBAC directly onto the partner's shared secure views.

Answer: C

Explanation:
According to the Snowflake documentation1, secure views are only exposed to authorized users who have been granted the role that owns the view. Therefore, applying RBAC directly onto the partner's shared secure views (option A) is not possible, as the administrator does not own those views. Individually granting imported privileges onto the schema in the share (option B) is also not feasible, as the privileges granted on the schema do not apply to existing secure views, only to future ones2. Cloning the data and inserting it into a company-owned share (option C) is not recommended, as it would create unnecessary duplication of data and increase storage costs. The best option is to create views over the incoming shared database and apply the desired RBAC onto these views (option D). This way, the administrator can control the access to the data based on the roles in their account, without modifying the original data or views from the partner.


NEW QUESTION # 40
What are characteristics of Dynamic Data Masking? (Select TWO).

  • A. A masking policy that is currently set on a table can be dropped.
  • B. A masking policy can be applied to the VALUE column of an external table.
  • C. A single masking policy can be applied to columns in different tables.
  • D. The role that creates the masking policy will always see unmasked data in query results.
  • E. A single masking policy can be applied to columns with different data types.

Answer: C,E

Explanation:
Explanation
According to the Using Dynamic Data Masking documentation, Dynamic Data Masking is a feature that allows you to alter sections of data in table and view columns at query time using a predefined masking strategy. The following are some of the characteristics of Dynamic Data Masking:
*A single masking policy can be applied to columns in different tables. This means that you can write a policy once and have it apply to thousands of columns across databases and schemas.
*A single masking policy can be applied to columns with different data types. This means that you can use the same masking strategy for columns that store different kinds of data, such as strings, numbers, dates, etc.
*A masking policy that is currently set on a table can be dropped. This means that you can remove the masking policy from the table and restore the original data visibility.
*A masking policy can be applied to the VALUE column of an external table. This means that you can mask data that is stored in an external stage and queried through an external table.
*The role that creates the masking policy will always see unmasked data in query results. This is not true, as the masking policy can also apply to the creator role depending on the execution context conditions defined in the policy. For example, if the policy specifies that only users with a certain custom entitlement can see the unmasked data, then the creator role will also need to have that entitlement to see the unmasked data.


NEW QUESTION # 41
A Snowflake Administrator needs to persist all virtual warehouse configurations for auditing and backups. Given a table already exists with the following schema:
Table Name : VWH_META
Column 1 : SNAPSHOT_TIME TIMESTAMP_NTZ
Column 2 : CONFIG VARIANT
Which commands should be executed to persist the warehouse data at the time of execution in JSON format in the table VWH META?

  • A. 1. SHOW WAREHOUSES;
    2. INSERT INTO VWH META
    SELECT CURRENT TIMESTAMP (), *
    FROM TABLE (RESULT_SCAN (LAST_QUERY_ID ())) ;
  • B. 1. SHOW WAREHOUSES;
    2. INSERT INTO VWH_META
    SELECT CURRENT_TIMESTAMP (),
    OBJECT CONSTRUCT (*)
    FROM TABLE (RESULT_SCAN (LAST_QUERY_ID ()));
  • C. 1. SHOW WAREHOUSES;
    2. INSERT INTO VWH META
    SELECT CURRENT TIMESTAMP (), *
    FROM TABLE (RESULT_SCAN (SELECT
    LAST QUERY ID(-1)));
  • D. 1. SHOW WAREHOUSES;
    2. INSERT INTO VWH META
    SELECT CURRENT TIMESTAMP (),
    FROM TABLE (RESULT_SCAN (LAST_QUERY_ID(1) ) ) ;

Answer: B

Explanation:
According to the Using Persisted Query Results documentation, the RESULT_SCAN function allows you to query the result set of a previous command as if it were a table. The LAST_QUERY_ID function returns the query ID of the most recent statement executed in the current session. Therefore, the combination of these two functions can be used to access the output of the SHOW WAREHOUSES command, which returns the configurations of all the virtual warehouses in the account. However, to persist the warehouse data in JSON format in the table VWH_META, the OBJECT_CONSTRUCT function is needed to convert the output of the SHOW WAREHOUSES command into a VARIANT column. The OBJECT_CONSTRUCT function takes a list of key-value pairs and returns a single JSON object. Therefore, the correct commands to execute are:
1. SHOW WAREHOUSES;
2. INSERT INTO VWH_META SELECT CURRENT_TIMESTAMP (), OBJECT_CONSTRUCT (*) FROM TABLE (RESULT_SCAN (LAST_QUERY_ID ())); The other options are incorrect because:
* A. This option does not use the OBJECT_CONSTRUCT function, so it will not persist the warehouse data in JSON format. Also, it is missing the * symbol in the SELECT clause, so it will not select any columns from the result set of the SHOW WAREHOUSES command.
* B. This option does not use the OBJECT_CONSTRUCT function, so it will not persist the warehouse data in JSON format. It will also try to insert multiple columns into a single VARIANT column, which will cause a type mismatch error.
* D. This option does not use the OBJECT_CONSTRUCT function, so it will not persist the warehouse data in JSON format. It will also try to use the RESULT_SCAN function on a subquery, which is not supported. The RESULT_SCAN function can only be used on a query ID or a table name.


NEW QUESTION # 42
......

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