2026 Valid ADA-C01 Exam Updates - 2026 Study Guide
ADA-C01 Certification - The Ultimate Guide [Updated 2026]
Snowflake ADA-C01 Exam Syllabus Topics:
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NEW QUESTION # 37
The ACCOUNTADMIN of Account 123 works with Snowflake Support to set up a Data Exchange. After the exchange is populated with listings from other Snowflake accounts, what roles in Account 123 are allowed to request and get data?
- A. Only the ACCOUNTADMIN role, and no other roles
- B. Any role that the listing provider has designated as authorized
- C. Any role with USAGE privilege on the Data Exchange
- D. Any role with IMPORT SHARE and CREATE DATABASE privileges
Answer: C
Explanation:
To request and get data from a Data Exchange, the role in Account 123 must have the USAGE privilege on the Data Exchange object. This privilege allows the role to view the listings and request access to the data. According to the Snowflake documentation, "To view the listings in a data exchange, a role must have the USAGE privilege on the data exchange object. To request access to a listing, a role must have the USAGE privilege on the data exchange object and the IMPORT SHARE privilege on the account." The other options are either incorrect or not sufficient to request and get data from a Data Exchange. Option A is incorrect, as the ACCOUNTADMIN role is not the only role that can request and get data, as long as other roles have the necessary privileges. Option C is incorrect, as the IMPORT SHARE and CREATE DATABASE privileges are not required to request and get data, but only to create a database from a share after the access is granted. Option D is incorrect, as the listing provider does not designate the authorized roles in Account 123, but only approves or denies the requests from Account 123.
NEW QUESTION # 38
A Snowflake Administrator needs to set up Time Travel for a presentation area that includes facts and dimensions tables, and receives a lot of meaningless and erroneous loT dat a. Time Travel is being used as a component of the company's data quality process in which the ingestion pipeline should revert to a known quality data state if any anomalies are detected in the latest load. Data from the past 30 days may have to be retrieved because of latencies in the data acquisition process.
According to best practices, how should these requirements be met? (Select TWO).
- A. Only TRANSIENT tables should be used to ensure referential integrity between the fact and dimension tables.
- B. The fact and dimension tables should have the same DATA_RETENTION_TIME_IN_ DAYS.
- C. Related data should not be placed together in the same schema. Facts and dimension tables should each have their own schemas.
- D. The DATA_RETENTION_TIME_IN_DAYS should be kept at the account level and never used for lower level containers (databases and schemas).
- E. The fact and dimension tables should be cloned together using the same Time Travel options to reduce potential referential integrity issues with the restored data.
Answer: B,E
Explanation:
According to the Understanding & Using Time Travel documentation, Time Travel is a feature that allows you to query, clone, and restore historical data in tables, schemas, and databases for up to 90 days. To meet the requirements of the scenario, the following best practices should be followed:
* The fact and dimension tables should have the same DATA_RETENTION_TIME_IN_DAYS. This parameter specifies the number of days for which the historical data is preserved and can be accessed by Time Travel. To ensure that the fact and dimension tables can be reverted to a consistent state in case of any anomalies in the latest load, they should have the same retention period. Otherwise, some tables may lose their historical data before others, resulting in data inconsistency and quality issues.
* The fact and dimension tables should be cloned together using the same Time Travel options to reduce potential referential integrity issues with the restored data. Cloning is a way of creating a copy of an object (table, schema, or database) at a specific point in time using Time Travel. To ensure that the fact and dimension tables are cloned with the same data set, they should be cloned together using the same AT or BEFORE clause. This will avoid any referential integrity issues that may arise from cloning tables at different points in time.
The other options are incorrect because:
* Related data should not be placed together in the same schema. Facts and dimension tables should each have their own schemas. This is not a best practice for Time Travel, as it does not affect the ability to query, clone, or restore historical data. However, it may be a good practice for data modeling and organization, depending on the use case and design principles.
* The DATA_RETENTION_TIME_IN_DAYS should be kept at the account level and never used for lower level containers (databases and schemas). This is not a best practice for Time Travel, as it limits the flexibility and granularity of setting the retention period for different objects. The retention period can be set at the account, database, schema, or table level, and the most specific setting overrides the more general ones. This allows for customizing the retention period based on the data needs and characteristics of each object.
* Only TRANSIENT tables should be used to ensure referential integrity between the fact and dimension tables. This is not a best practice for Time Travel, as it does not affect the referential integrity between the tables. Transient tables are tables that do not have a Fail-safe period, which means that they cannot be recovered by Snowflake after the retention period ends. However, they still support Time Travel within the retention period, and can be queried, cloned, and restored like permanent tables. The choice of table type depends on the data durability and availability requirements, not on the referential integrity.
NEW QUESTION # 39
The following SQL command was executed:
Use role SECURITYADMIN;
Grant ownership
On future tables
In schema PROD. WORKING
To role PROD_WORKING_OWNER;
Grant role PROD_WORKING_OWNER to role SYSADMIN;
Use role ACCOUNTADMIN;
Create table PROD.WORKING.XYZ (value number) ;
Which role(s) can alter or drop table XYZ?
- A. Only the PROD_WORKING_OWNER role can alter or drop table XYZ.
- B. Because ACCOUNTADMIN created the table, only the ACCOUNTADMIN role can alter or drop table XYZ.
- C. SECURITYADMIN, SYSADMIN, and ACCOUNTADMIN can alter or drop table XYZ.
- D. PROD_WORKING_OWNER, ACCOUNTADMIN, and SYSADMIN can alter or drop table XYZ.
Answer: D
Explanation:
Explanation
According to the GRANT OWNERSHIP documentation, the ownership privilege grants full control over the table and can only be held by one role at a time. However, the current owner can also grant the ownership privilege to another role, which transfers the ownership to the new role. In this case, the SECURITYADMIN role granted the ownership privilege on future tables in the PROD.WORKING schema to the PROD_WORKING_OWNER role. This means that any table created in that schema after the grant statement will be owned by the PROD_WORKING_OWNER role. Therefore, the PROD_WORKING_OWNER role can alter or drop table XYZ, which was created by the ACCOUNTADMIN role in the PROD.WORKING schema. Additionally, the ACCOUNTADMIN role can also alter or drop table XYZ, because it is the top-level role that has all privileges on all objects in the account. Furthermore, the SYSADMIN role can also alter or drop table XYZ, because it was granted the PROD_WORKING_OWNER role by the SECURITYADMIN role. The SYSADMIN role can activate the PROD_WORKING_OWNER role and inherit its privileges, including the ownership privilege on table XYZ. The SECURITYADMIN role cannot alter or drop table XYZ, because it does not have the ownership privilege on the table, nor does it have the PROD_WORKING_OWNER role.
NEW QUESTION # 40
A Snowflake customer is experiencing higher costs than anticipated while migrating their data warehouse workloads from on-premises to Snowflake. The migration workloads have been deployed on a single warehouse and are characterized by a large number of small INSERTs rather than bulk loading of large extracts. That single warehouse has been configured as a single cluster, 2XL because there are many parallel INSERTs that are scheduled during nightly loads.
How can the Administrator reduce the costs, while minimizing the overall load times, for migrating data warehouse history?
- A. There should be another 2XL warehouse deployed to handle a portion of the load queries.
- B. The INSERTS should be converted to several tables to avoid contention on large tables that slows down query processing.
- C. The warehouse should be kept as a SMALL or XSMALL and configured as a multi-cluster warehouse to handle the parallel load queries.
- D. The 2XL warehouse should be changed to 4XL to increase the number of threads available for parallel load queries.
Answer: C
Explanation:
According to the Snowflake Warehouse Cost Optimization blog post, one of the strategies to reduce the cost of running a warehouse is to use a multi-cluster warehouse with auto-scaling enabled. This allows the warehouse to automatically adjust the number of clusters based on the concurrency demand and the queue size. A multi-cluster warehouse can also be configured with a minimum and maximum number of clusters, as well as a scaling policy to control the scaling behavior. This way, the warehouse can handle the parallel load queries efficiently without wasting resources or credits. The blog post also suggests using a smaller warehouse size, such as SMALL or XSMALL, for loading data, as it can perform better than a larger warehouse size for small INSERTs. Therefore, the best option to reduce the costs while minimizing the overall load times for migrating data warehouse history is to keep the warehouse as a SMALL or XSMALL and configure it as a multi-cluster warehouse to handle the parallel load queries. The other options are incorrect because:
* A. Deploying another 2XL warehouse to handle a portion of the load queries will not reduce the costs, but increase them. It will also introduce complexity and potential inconsistency in managing the data loading process across multiple warehouses.
* B. Changing the 2XL warehouse to 4XL will not reduce the costs, but increase them. It will also provide more compute resources than needed for small INSERTs, which are not CPU-intensive but I/O-intensive.
* D. Converting the INSERTs to several tables will not reduce the costs, but increase them. It will also create unnecessary data duplication and fragmentation, which will affect the query performance and data quality.
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 (SELECT
LAST QUERY ID(-1))); - B. 1. SHOW WAREHOUSES;
2. INSERT INTO VWH META
SELECT CURRENT TIMESTAMP (), *
FROM TABLE (RESULT_SCAN (LAST_QUERY_ID ())) ; - C. 1. SHOW WAREHOUSES;
2. INSERT INTO VWH_META
SELECT CURRENT_TIMESTAMP (),
OBJECT CONSTRUCT (*)
FROM TABLE (RESULT_SCAN (LAST_QUERY_ID ())); - D. 1. SHOW WAREHOUSES;
2. INSERT INTO VWH META
SELECT CURRENT TIMESTAMP (),
FROM TABLE (RESULT_SCAN (LAST_QUERY_ID(1) ) ) ;
Answer: C
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
.
Company A uses Snowflake to manage audio files of call recordings. Company A hired Company B, who also uses Snowflake, to transcribe the audio files for further analysis.
Company A's Administrator created a share.
What object should be added to the share to allow Company B access to the files?
- A. A secure view with a column for METADATA$FILENAME.
- B. A secure view with a column for file URLs.
- C. A secure view with a column for the stage name and a column for the file path.
- D. A secure view with a column for pre-signed URLs.
Answer: D
Explanation:
Explanation
According to the Snowflake documentation1, pre-signed URLs are required to access external files in a share.
A secure view can be used to generate pre-signed URLs for the audio files stored in an external stage and expose them to the consumer account. Option A is incorrect because file URLs alone are not sufficient to access external files in a share. Option C is incorrect because METADATA$FILENAME only returns the file name, not the full path or URL. Option D is incorrect because the stage name and file path are not enough to generate pre-signed URLs.
NEW QUESTION # 43
What are benefits of using Snowflake organizations? (Select TWO).
- A. User administration is simplified across all accounts within the organization.
- B. Administrators can change Snowflake account editions on-demand based on need.
- C. Administrators can simplify data movement across all accounts within the organization.
- D. Administrators can monitor and understand usage across all accounts in the organization.
- E. Administrators have the ability to create accounts in any available cloud provider or region.
Answer: D,E
Explanation:
Explanation
According to the Snowflake documentation1, organizations are a feature that allows linking the accounts owned by a business entity, simplifying account management and billing, replication and failover, data sharing, and other account administration tasks. Some of the benefits of using organizations are:
*Administrators can monitor and understand usage across all accounts in the organization using the ORGANIZATION_USAGE schema, which provides historical usage data for all accounts in the organization via views in a shared database named SNOWFLAKE2. This can help to optimize costs and performance across the organization.
*Administrators have the ability to create accounts in any available cloud provider or region using the CREATE ACCOUNT command, which allows specifying the cloud platform and region for the new account3.
This can help to meet the business needs and compliance requirements of the organization.
Option A is incorrect because administrators cannot change Snowflake account editions on-demand based on need, but rather have to contact Snowflake Support to request an edition change4. Option C is incorrect because administrators cannot simplify data movement across all accounts within the organization, but rather have to enable account database replication for both the source and target accounts, and use the ALTER DATABASE ... ENABLE REPLICATION TO ACCOUNTS command to promote a local database to serve as the primary database and enable replication to the target accounts5. Option D is incorrect because user administration is not simplified across all accounts within the organization, but rather requires creating and managing users, roles, and privileges for each account separately, unless using a federated authentication method such as SSO or SCIM.
NEW QUESTION # 44
What are benefits of creating and maintaining resource monitors in Snowflake? (Select THREE).
- A. Multiple triggers can be configured across various virtual warehouse thresholds.
- B. Resource monitors can be applied to more than one virtual warehouse.
- C. Resource monitor governance is tightly controlled and monitors can only be created by the ACCOUNTADMIN role or users with the CREATE MONITOR privilege.
- D. Resource monitors add no additional load to virtual warehouse compute.
- E. Multiple resource monitors can be applied to a single virtual warehouse.
- F. The cost of running a resource monitor is only 10% of a credit, per day of operation.
Answer: A,B,D
Explanation:
According to the Snowflake documentation1, resource monitors are a feature that helps you manage and control Snowflake costs by monitoring and setting limits on your compute resources. Resource monitors do not consume any credits or add any load to the virtual warehouses they monitor1. Resource monitors can also have multiple triggers that specify different actions (such as suspending or notifying) when certain percentages of the credit quota are reached2. Resource monitors can be applied to either the entire account or a specific set of individual warehouses1. The other options are not benefits of resource monitors. The cost of running a resource monitor is negligible, not 10% of a credit3. Multiple resource monitors cannot be applied to a single virtual warehouse; only one resource monitor can be assigned to a warehouse at a time2. Resource monitor governance is not tightly controlled; account administrators can enable users with other roles to view and modify resource monitors using SQL2.
NEW QUESTION # 45
What are the MINIMUM grants required on the database, schema, and table for a stream to be properly created and managed?
- A. Database: Usage, Create Stream
Schema: Usage
Table: Select - B. Database: Usage
Schema: Usage
Table: Select - C. Database: Usage
Schema: Usage, Create Stream
Table: Select - D. Database: Usage
Schema: Usage
Table: Select, Create Stream
Answer: D
NEW QUESTION # 46
A Snowflake Administrator needs to set up Time Travel for a presentation area that includes facts and dimensions tables, and receives a lot of meaningless and erroneous loT data. Time Travel is being used as a component of the company's data quality process in which the ingestion pipeline should revert to a known quality data state if any anomalies are detected in the latest load. Data from the past 30 days may have to be retrieved because of latencies in the data acquisition process.
According to best practices, how should these requirements be met? (Select TWO).
- A. Only TRANSIENT tables should be used to ensure referential integrity between the fact and dimension tables.
- B. The fact and dimension tables should have the same DATA_RETENTION_TIME_IN_ DAYS.
- C. Related data should not be placed together in the same schema. Facts and dimension tables should each have their own schemas.
- D. The DATA_RETENTION_TIME_IN_DAYS should be kept at the account level and never used for lower level containers (databases and schemas).
- E. The fact and dimension tables should be cloned together using the same Time Travel options to reduce potential referential integrity issues with the restored data.
Answer: B,E
Explanation:
Explanation
According to the Understanding & Using Time Travel documentation, Time Travel is a feature that allows you to query, clone, and restore historical data in tables, schemas, and databases for up to 90 days. To meet the requirements of the scenario, the following best practices should be followed:
*The fact and dimension tables should have the same DATA_RETENTION_TIME_IN_DAYS. This parameter specifies the number of days for which the historical data is preserved and can be accessed by Time Travel. To ensure that the fact and dimension tables can be reverted to a consistent state in case of any anomalies in the latest load, they should have the same retention period. Otherwise, some tables may lose their historical data before others, resulting in data inconsistency and quality issues.
*The fact and dimension tables should be cloned together using the same Time Travel options to reduce potential referential integrity issues with the restored data. Cloning is a way of creating a copy of an object (table, schema, or database) at a specific point in time using Time Travel. To ensure that the fact and dimension tables are cloned with the same data set, they should be cloned together using the same AT or BEFORE clause. This will avoid any referential integrity issues that may arise from cloning tables at different points in time.
The other options are incorrect because:
*Related data should not be placed together in the same schema. Facts and dimension tables should each have their own schemas. This is not a best practice for Time Travel, as it does not affect the ability to query, clone, or restore historical data. However, it may be a good practice for data modeling and organization, depending on the use case and design principles.
*The DATA_RETENTION_TIME_IN_DAYS should be kept at the account level and never used for lower level containers (databases and schemas). This is not a best practice for Time Travel,as it limits the flexibility and granularity of setting the retention period for different objects. The retention period can be set at the account, database, schema, or table level, and the most specific setting overrides the more general ones. This allows for customizing the retention period based on the data needs and characteristics of each object.
*Only TRANSIENT tables should be used to ensure referential integrity between the fact and dimension tables. This is not a best practice for Time Travel, as it does not affect the referential integrity between the tables. Transient tables are tables that do not have a Fail-safe period, which means that they cannot be recovered by Snowflake after the retention period ends. However, they still support Time Travel within the retention period, and can be queried, cloned, and restored like permanent tables. The choice of table type depends on the data durability and availability requirements, not on the referential integrity.
NEW QUESTION # 47
What are benefits of using Snowflake organizations? (Select TWO).
- A. User administration is simplified across all accounts within the organization.
- B. Administrators can change Snowflake account editions on-demand based on need.
- C. Administrators can simplify data movement across all accounts within the organization.
- D. Administrators can monitor and understand usage across all accounts in the organization.
- E. Administrators have the ability to create accounts in any available cloud provider or region.
Answer: D,E
Explanation:
According to the Snowflake documentation1, organizations are a feature that allows linking the accounts owned by a business entity, simplifying account management and billing, replication and failover, data sharing, and other account administration tasks. Some of the benefits of using organizations are:
* Administrators can monitor and understand usage across all accounts in the organization using the ORGANIZATION_USAGE schema, which provides historical usage data for all accounts in the organization via views in a shared database named SNOWFLAKE2. This can help to optimize costs and performance across the organization.
* Administrators have the ability to create accounts in any available cloud provider or region using the CREATE ACCOUNT command, which allows specifying the cloud platform and region for the new account3. This can help to meet the business needs and compliance requirements of the organization.
Option A is incorrect because administrators cannot change Snowflake account editions on-demand based on need, but rather have to contact Snowflake Support to request an edition change4. Option C is incorrect because administrators cannot simplify data movement across all accounts within the organization, but rather have to enable account database replication for both the source and target accounts, and use the ALTER DATABASE ... ENABLE REPLICATION TO ACCOUNTS command to promote a local database to serve as the primary database and enable replication to the target accounts5. Option D is incorrect because user administration is not simplified across all accounts within the organization, but rather requires creating and managing users, roles, and privileges for each account separately, unless using a federated authentication method such as SSO or SCIM.
NEW QUESTION # 48
What are characteristics of data replication in Snowflake? (Select THREE).
- A. Users must be granted REPLICATIONADMIN privileges in order to enable replication.
- B. Replication can only occur within the same cloud provider.
- C. The ALTER DATABASE ... ENABLE REPLICATION TO ACCOUNTS command must be issued from the primary account.
- D. Databases created from shares can be replicated.
- E. To start replication run the ALTER DATABASE ... REFRESH command on the account where the secondary database resides.
- F. Users can have unlimited primary databases and they can be replicated to an unlimited number of accounts if all accounts are within the same organization.
Answer: C,D,F
Explanation:
Explanation
*Option A is correct because the ALTER DATABASE ... ENABLE REPLICATION TO ACCOUNTS command must be issued from the primary account that owns the database to be replicated1.
*Option B is incorrect because users must be granted REPLICATIONGRANTER privileges in order to enable replication1.
*Option C is incorrect because to start replication, the ALTER DATABASE ... REFRESH command must be run on the primary database, not the secondary database1.
*Option D is incorrect because replication can occur across different cloud providers, as well as across regions2.
*Option E is correct because databases created from shares can be replicated, as long as the share is active and the database is not dropped or altered1.
*Option F is correct because users can have unlimited primary databases and they can be replicated to an unlimited number of accounts if all accounts are within the same organization1.
NEW QUESTION # 49
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 (SELECT
LAST QUERY ID(-1))); - B. 1. SHOW WAREHOUSES;
2. INSERT INTO VWH META
SELECT CURRENT TIMESTAMP (), *
FROM TABLE (RESULT_SCAN (LAST_QUERY_ID ())) ; - C. 1. SHOW WAREHOUSES;
2. INSERT INTO VWH_META
SELECT CURRENT_TIMESTAMP (),
OBJECT CONSTRUCT (*)
FROM TABLE (RESULT_SCAN (LAST_QUERY_ID ())); - D. 1. SHOW WAREHOUSES;
2. INSERT INTO VWH META
SELECT CURRENT TIMESTAMP (),
FROM TABLE (RESULT_SCAN (LAST_QUERY_ID(1) ) ) ;
Answer: C
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. 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 # 50
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 (SELECT
LAST QUERY ID(-1))); - B. 1. SHOW WAREHOUSES;
2. INSERT INTO VWH META
SELECT CURRENT TIMESTAMP (), *
FROM TABLE (RESULT_SCAN (LAST_QUERY_ID ())) ; - C. 1. SHOW WAREHOUSES;
2. INSERT INTO VWH_META
SELECT CURRENT_TIMESTAMP (),
OBJECT CONSTRUCT (*)
FROM TABLE (RESULT_SCAN (LAST_QUERY_ID ())); - D. 1. SHOW WAREHOUSES;
2. INSERT INTO VWH META
SELECT CURRENT TIMESTAMP (),
FROM TABLE (RESULT_SCAN (LAST_QUERY_ID(1) ) ) ;
Answer: C
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 # 51
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. USE ROLE ROLE MANAGED_ACCESS;
DROP SCHEMA WORK. SCHEMA_MANAGED_ACCESS;
CREATE SCHEMA SCHEMA_MANAGED_ACCESS;
Then recreate all needed objects. - B. ALTER SCHEMA SCHEMA MANAGED ACCESS DISABLE MANAGED ACCESS;
- C. REVOKE SELECT, INSERT ON FUTURE TABLES IN SCHEMA SCHEMA_MANAGED_ACCESS FROM ROLE_MANAGED_ACCESS; ALTER SCHEMA SCHEMA MANAGED ACCESS DISABLE MANAGED ACCESS;
- 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: B
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 # 52
Which actions are considered breaking changes to data that is shared with consumers in the Snowflake Marketplace? (Select TWO).
- A. Unpublishing the data listing
- B. Deleting data from a table
- C. Dropping a column from a table
- D. Renaming a table
- E. Adding region availability to the listing
Answer: C,D
Explanation:
According to the Snowflake documentation1, breaking changes are changes that affect the schema or structure of the shared data, such as dropping or renaming a column or a table. These changes may cause errors or unexpected results for the consumers who query the shared data. Deleting data from a table, unpublishing the data listing, or adding region availability to the listing are not breaking changes, as they do not alter the schema or structure of the shared data.
1: Managing Data Listings in Snowflake Data Marketplace | Snowflake Documentation
NEW QUESTION # 53
A company has many users in the role ANALYST who routinely query Snowflake through a reporting tool.
The Administrator has noticed that the ANALYST users keep two
small clusters busy all of the time, and occasionally they need three or four clusters of that size.
Based on this scenario, how should the Administrator set up a virtual warehouse to MOST efficiently support this group of users?
- A. Create four virtual warehouses (sized Small through XL) and set them to auto-suspend and auto-resume.Have users in the ANALYST role select the appropriate warehouse based on how many queries are being run.
- B. Create a multi-cluster warehouse with MIN_CLUSTERS set to 1. Give MANAGE privileges to the ANALYST role so this group can start and stop the warehouse, and increase the number of clusters as needed.
- C. Create a multi-cluster warehouse with MIN_CLUSTERS set to 2. Set the warehouse to auto-resume and auto-suspend, and give USAGE privileges to the ANALYST role. Allow the warehouse to auto-scale.
- D. Create a standard X-Large warehouse, which is equivalent to four small clusters. Set the warehouse to auto-resume and auto-suspend, and give USAGE privileges to the ANALYST role.
Answer: C
Explanation:
Explanation
According to the Snowflake documentation1, a multi-cluster warehouse is a virtual warehouse that consists of multiple clusters of compute resources that can scale up or down automatically to handle the concurrency and performance needs of the queries submitted to the warehouse. A multi-cluster warehouse has a minimum and maximum number of clusters that can be specified by the administrator. Option B is the most efficient way to support the group of users, as it allows the administrator to create a multi-cluster warehouse with MIN_CLUSTERS set to 2, which means that the warehouse will always have two clusters running to handle the standard workload. The warehouse can also auto-scale up to the maximum number of clusters (which can be set according to the peak workload) when there is a spike in demand, and then scale down when the demand decreases. The warehouse can also auto-resume and auto-suspend, which means that the warehouse will automatically start when a query is submitted and automatically stop after a period of inactivity. The administrator can also give USAGE privileges to the ANALYST role, which means that the users can use the warehouse to execute queries and load data, but not modify or operate the warehouse. Option A is not efficient, as it requires the users to manually start and stop the warehouse, and increase the number of clusters as needed, which can be time-consuming and error-prone. Option C is not efficient, as it creates a standard X-Large warehouse, which is equivalent to four small clusters, which may be more than needed for the standard workload, and may not be enough for the peak workload. Option D is not efficient, as it creates four virtual warehouses of different sizes, which can be confusing and cumbersome for the users to select the appropriate warehouse based on how many queries are being run, and may also result in wasted resources and costs.
NEW QUESTION # 54
Which function is the role SECURITYADMIN responsible for that is not granted to role USERADMIN?
- A. Manage system grants
- B. Create new users
- C. Reset a Snowflake user's password
- D. Create new roles
Answer: A
Explanation:
According to the Snowflake documentation1, the SECURITYADMIN role is responsible for managing all grants on objects in the account, including system grants. The USERADMIN role can only create and manage users and roles, but not grant privileges on other objects. Therefore, the function that is unique to the SECURITYADMIN role is to manage system grants. Option A is incorrect because both roles can reset a user's password. Option C is incorrect because both roles can create new users. Option D is incorrect because both roles can create new roles.
NEW QUESTION # 55
Which command can temporarily disable Multi-factor Authentication (MFA) for the Snowflake username user1 for 24 hours?
- A. alter user userl set TEMPORARY_MFA_BYPASS=1440;
- B. alter user userl set MINS_TO_BYPASS_MFA=1440;
- C. alter user userl set DISABLE_MFA=1440;
- D. alter user userl set HOURS_TO_BYPASS_MFA=24;
Answer: B
Explanation:
Explanation
According to the Snowflake documentation1, the MINS_TO_BYPASS_MFA property specifies the number of minutes to temporarily disable MFA for a user so that they can log in without the temporary token generated by the Duo Mobile application. After the time passes, MFA is enforced and the user cannot log in without the token. Therefore, to disable MFA for 24 hours, the value of this property should be set to 1440 minutes (24 x
60). Option B is incorrect because the DISABLE_MFA property is a boolean value that permanently disables MFA for a user, not a numeric value that specifies the duration. Option C is incorrect because there is no such property as TEMPORARY_MFA_BYPASS in Snowflake. Option D is incorrect because there is no such property as HOURS_TO_BYPASS_MFA in Snowflake.
NEW QUESTION # 56
Which masking policy will mask a column whenever it is queried through a view owned by a role named MASKED_VIEW_ROLE?
- A. create or replace masking policy maskString as (val string) returns string -> case when array_contains ('MASKED_VIEW_ROLE' :: variant, parse_json (current_available_roles ())) then '* else val end;
** ' - B. create or replace masking policy maskString as (val string) returns string -> case when current_role() in ('MASKED_VIEW_ROLE') then ' ********* ' else val end;
- C. create or replace masking policy maskstring as (val string) returns string -> case when invoker_role() in ('MASKED_VIEW_ROLE') then else val end;
' ** - D. create or replace masking policy maskstring as (val string) returns string -> case when is_role_in_session ('MASKED_VIEW_ROLE') then ' ** else val end;
*,
Answer: D
Explanation:
A masking policy is a SQL expression that transforms the data in a column based on the role that queries the column1. The is_role_in_session function returns true if the specified role is in the current session2. Therefore, the masking policy in option A will mask the column data with asterisks whenever it is queried through a view owned by the MASKED_VIEW_ROLE3. The other options use different functions that do not check the ownership of the view, but rather the current role, the invoker role, or the available roles in the session45. These functions may not return the desired result if the role that owns the view is different from the role that queries the view.
NEW QUESTION # 57
An Administrator needs to implement an access control mechanism across an organization. The organization users access sensitive customer data that comes from different regions and needs to be accessible for Analysts who work in these regions. Some Analysts need very specific access control depending on their functional roles in the organization. Following Snowflake recommended practice, how should these requirements be met? (Select TWO).
- A. Use zero-copy cloning to replicate the database schema and provide access as needed.
- B. Implement views on top of base tables that exclude or mask sensitive data.
- C. Use a third-party tool to share the data.
- D. Implement row access policies and Dynamic Data Masking policies.
- E. Include masking rules as part of data ingestion and transformation pipelines.
Answer: B,D
Explanation:
The scenario describes a need for fine-grained access control over sensitive customer data across multiple regions, with functional-role-based access for analysts. Snowflake recommends applying a layered security model that separates raw data from user-facing access and leverages built-in policy features.
Explanation of Correct Answers:
A . Implement views on top of base tables that exclude or mask sensitive data.
Creating secure views allows administrators to abstract sensitive fields or filter out certain rows and columns.
It enables role-based access control by granting specific roles access only to the secure views.
Common practice is to restrict access to base tables and give users access to views that enforce business logic and data access rules.
B . Implement row access policies and Dynamic Data Masking policies.
Row Access Policies control access at the row level, determining what data a user can see based on their role or session context.
Dynamic Data Masking allows you to mask sensitive column data (like PII) dynamically based on the accessing role.
Both are central features of Snowflake's fine-grained access control.
Why the other options are incorrect:
C . Include masking rules as part of data ingestion and transformation pipelines.
This is not a Snowflake-recommended best practice for access control.
It hardcodes data access rules into ETL/ELT logic, which reduces flexibility and central control.
Also, it masks the data permanently at ingestion time, rather than dynamically at query time.
D . Use a third-party tool to share the data.
Snowflake supports native Secure Data Sharing, and using a third-party tool is unnecessary and introduces complexity.
It does not address row/column-level access control within Snowflake itself.
E . Use zero-copy cloning to replicate the database schema and provide access as needed.
Zero-copy cloning is ideal for testing, development, and backup purposes, not for controlling access.
It duplicates metadata but doesn't provide a mechanism for fine-grained, real-time access control.
SnowPro Administrator Reference:
Row Access Policies Overview
Dynamic Data Masking Overview
Access Control Best Practices
Using Secure Views for Access Control
NEW QUESTION # 58
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