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Snowflake ADA-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	Given a scenario, create and manage access control Given a scenario, implement resource monitors
Topic 2	Set up and manage network and private connectivity Given a scenario, manage Snowflake Time Travel and Fail-safe
Topic 3	Given a scenario, configure access controls Set up and manage security administration and authorization
Topic 4	Interpret and make recommendations for data clustering Manage DML locking and concurrency in Snowflake
Topic 5	Implement and manage data governance in Snowflake Data Sharing, Data Exchange, and Snowflake Marketplace

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Snowflake SnowPro Advanced Administrator Sample Questions (Q76-Q81):

NEW QUESTION # 76
What are characteristics of Dynamic Data Masking? (Select TWO).

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

Answer: A,B

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 # 77
Which commands can be performed by a user with the ORGADMIN role but not the ACCOUNTADMIN role? (Select TWO).

A. SHOW USERS;
B. SELECT SYSTEM$GLOBAL_ACCOUNT_SET_PARAMETER (
'ACCOUNT LOCATOR',
'ENABLE ACCOUNT DATABASE_REPLICATION',
'true'
);
C. SHOW ORGANIZATION ACCOUNTS;
D. GRANT ROLE ORGADMIN TO USER <username>;
E. SHOW REGIONS;

Answer: B,C

Explanation:
Explanation
According to the Snowflake documentation1, the ORGADMIN role is a special system role that is responsible for managing operations at the organization level, such as creating and viewing accounts, enabling database replication, and setting global account parameters. The ACCOUNTADMIN role is a system role that is responsible for managing operations at the account level, such as creating and managing users, roles, warehouses, databases, and shares. Therefore, the commands that can be performed by the ORGADMIN role but not the ACCOUNTADMIN role are:
*SHOW ORGANIZATION ACCOUNTS: This command lists all the accounts in the organization and their properties, such as region, edition, and status2. The ACCOUNTADMIN role can only show the current account and its properties using the SHOW ACCOUNTS command3.
*SELECT SYSTEM$GLOBAL_ACCOUNT_SET_PARAMETER: This function sets a global account parameter for an account in the organization, such as enabling account database replication4. The ACCOUNTADMIN role can only set local account parameters using the ALTER ACCOUNT command.
Option A is incorrect because the SHOW REGIONS command can be executed by any role, not just the ORGADMIN role. Option B is incorrect because the SHOW USERS command can be executed by the ACCOUNTADMIN role, as well as any role that has been granted the MONITOR privilege on the account.
Option D is incorrect because the GRANT ROLE ORGADMIN TO USER <username> command can be executed by the ACCOUNTADMIN role, as well as any role that has been granted the ORGADMIN role1.

NEW QUESTION # 78
What is required for stages, without credentials, to limit data exfiltration after a storage integration and associated stages are created?

A. ALTER ACCOUNT my_account SET
REQUIRE_STORAGE_INTEGRATION_FOR_STAGE_CREATION = false;
ALTER ACCOUNT my_account SET
REQUIRE_STORAGE_INTEGRATION_FOR_STAGE_OPERATION = false;
ALTER ACCOUNT my_account SET
PREVENT_UNLOAD_TO_INLINE_URL = false;
B. ALTER ACCOUNT my_account SET
REQUIRE_STORAGE_INTEGRATION_FOR_STAGE_CREATION = false;
ALTER ACCOUNT my_account SET
REQUIRE_STORAGE_INTEGRATION_FOR_STAGE_OPERATION = false;
ALTER ACCOUNT my_account SET
PREVENT_UNLOAD_TO_INLINE_URL = true;
C. ALTER ACCOUNT my_account SET
REQUIRE_STORAGE_INTEGRATION_FOR_STAGE_CREATION = true;
ALTER ACCOUNT my_account SET
REQUIRE_STORAGE_INTEGRATION FOR STAGE_OPERATION = true;
ALTER ACCOUNT my_account SET
PREVENT_UNLOAD_TO_INLINE_URL = true;
D. ALTER ACCOUNT my_account SET
REQUIRE_STORAGE_INTEGRATION_FOR_STAGE_CREATION = true;
ALTER ACCOUNT my_account SET
REQUIRE_STORAGE_INTEGRATION_FOR_STAGE_OPERATION = true;
ALTER ACCOUNT my_account SET
PREVENT_UNLOAD_TO_INLINE_URL = false;

Answer: C

Explanation:
Explanation
According to the Snowflake documentation1, stages without credentials are a way to create external stages that use storage integrations to access data files in cloud storage without providing any credentials to Snowflake.
Storage integrations are objects that define a trust relationship between Snowflake and a cloud provider, allowing Snowflake to authenticate and authorize access to the cloud storage. To limit data exfiltration after a storage integration and associated stages are created, the following account-level parameters can be set:
*REQUIRE_STORAGE_INTEGRATION_FOR_STAGE_CREATION: This parameter enforces that all external stages must be created using a storage integration. This prevents users from creating external stages with inline credentials or URLs that point to unauthorized locations.
*REQUIRE_STORAGE_INTEGRATION_FOR_STAGE_OPERATION: This parameter enforces that all operations on external stages, such as PUT, GET, COPY, and LIST, must use a storage integration. This prevents users from performing operations on external stages with inline credentials or URLs that point to unauthorized locations.
*PREVENT_UNLOAD_TO_INLINE_URL: This parameter prevents users from unloading data from Snowflake tables to inline URLs that do not use a storage integration. This prevents users from exporting data to unauthorized locations.
Therefore, the correct answer is option D, which sets all these parameters to true. Option A is incorrect because it sets PREVENT_UNLOAD_TO_INLINE_URL to false, which allows users to unload data to inline URLs that do not use a storage integration. Option B is incorrect because it sets both REQUIRE_STORAGE_INTEGRATION_FOR_STAGE_CREATION and REQUIRE_STORAGE_INTEGRATION_FOR_STAGE_OPERATION to false, which allows users to create and operate on external stages without using a storage integration. Option C is incorrect because it sets all the parameters to false, which does not enforce any restrictions on data exfiltration.

NEW QUESTION # 79
If the query matches the definition, will Snowflake always dynamically rewrite the query to use a materialized view?

A. No, because the materialized view may not be up-to-date.
B. Yes, because materialized views are always faster.
C. No, because the optimizer might decide against it.
D. No, because joins are not supported by materialized views.

Answer: C

Explanation:
Snowflake's query optimizer can automatically rewrite queries against the base table or regular views to use the materialized view instead, if the query matches the definition of the materialized view1. However, this is not always guaranteed, as the optimizer might decide against using the materialized view based on various factors, such as the freshness of the data, the size of the result set, the complexity of the query, and the availability of the materialized view2. Therefore, the answer is no, because the optimizer might decide against it.

NEW QUESTION # 80
A Snowflake user runs a complex SQL query on a dedicated virtual warehouse that reads a large amount of data from micro-partitions. The same user wants to run another query that uses the same data set.
Which action would provide optimal performance for the second SQL query?

A. Increase the STATEMENT_TIMEOUT_IN_SECONDS parameter in the session.
B. Use the RESULT_SCAN function to post-process the output of the first query.
C. Assign additional clusters to the virtual warehouse.
D. Prevent the virtual warehouse from suspending between the running of the first and secondqueries.

Answer: B

Explanation:
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. This can improve the performance of the second query by avoiding reading the same data from micro-partitions again. The other actions do not provide optimal performance for the second query because:
*Assigning additional clusters to the virtual warehouse does not affect the data access speed, but only the query execution speed. It also increases the cost of the warehouse.
*Increasing the STATEMENT_TIMEOUT_IN_SECONDS parameter in the session does not improve the performance of the query, but only allows it to run longer before timing out. It also increases the risk of resource contention and deadlock.
*Preventing the virtual warehouse from suspending between the running of the first and second queries does not guarantee that the data will be cached in memory, as Snowflake uses a least recently used (LRU) cache eviction policy. It also increases the cost of the warehouse.
https://docs.snowflake.com/en/user-guide/querying-persisted-results

NEW QUESTION # 81
......

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100% Pass 2025 Marvelous Snowflake ADA-C01: SnowPro Advanced Administrator Trustworthy Practice

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Snowflake SnowPro Advanced Administrator Sample Questions (Q76-Q81):

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