Snowflake ADA-C01 Dumps

Option B is the correct answer because it follows the steps described in the Snowflake documentation for sharing data from multiple databases using secure views. The data provider needs to grant the REFERENCE_USAGE privilege on each database that contains objects referenced by the secure view, and the USAGE privilege only on the database where the secure view is created. Option A is incorrect because it grants the USAGE privilege instead of the REFERENCE_USAGE privilege. Option C is incorrect because it grants the REFERENCE_USAGE privilege to a database role, which is not supported. Option D is incorrect because it grants the REFERENCE_USAGE privilege on the wrong database.

According to the Snowflake documentation1, the MONITOR privilege on a warehouse grants the ability to view the warehouse usage and performance metrics, such as the number of credits consumed, the average and maximum run time, and the number of queries executed. The USAGE privilege on a warehouse grants the ability to use the warehouse to execute queries and load data. Therefore, the minimal privileges on the warehouse that should be granted to the role to meet the requirements for the application are MONITOR and USAGE. Option A is incorrect because the OPERATE privilege on a warehouse grants the ability to start, stop, resume, and suspend the warehouse, which is not required for the application. Option B is incorrect because the MODIFY privilege on a warehouse grants the ability to alter the warehouse properties, such as the size, auto-suspend, and auto-resume settings, which is not required for the application. Option E is incorrect because the OWNERSHIP privilege on a warehouse grants the ability to drop the warehouse, grant or revoke privileges on the warehouse, and transfer the ownership to another role, which is not required for the application.

According to the [GRANT MODIFY] documentation, the MODIFY privilege on a data exchange allows a role to perform administrative tasks on the data exchange, such as inviting members, approving profiles, and reviewing listings. This privilege can be granted by the ACCOUNTADMIN role or a role that already has the MODIFY privilege on the data exchange. Therefore, to delegate the administration of a company’s data exchange to users who do not have access to the ACCOUNTADMIN role, the best option is to grant the MODIFY privilege on the data exchange to a role that the users can assume. The other options are incorrect because:

•A. There is no such privilege as IMPORTED PRIVILEGES in Snowflake. The correct privilege name is IMPORT SHARE, which allows a role to create a database from a share. This privilege is not related to the administration of a data exchange, but to the consumption of shared data.

•C. There is no such privilege as OWNERSHIP in Snowflake. The correct privilege name is OWNED BY, which indicates the role that owns an object and has full control over it. However, this privilege cannot be granted or revoked, but only transferred by the current owner to another role using the GRANT OWNERSHIP command. Therefore, this option is not feasible for delegating the administration of a data exchange.

•D. The USAGE privilege on a data exchange allows a role to access the data exchange and view the available data listings. This privilege does not allow a role to perform administrative tasks on the data exchange, such as inviting members, approving profiles, and reviewing listings. Therefore, this option is not sufficient for delegating the administration of a data exchange.

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.

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.

Option B is the correct SQL command to create a resource monitor that meets the requirements. It sets the credit quota to 3000, the frequency to yearly, the start timestamp to January 1, 2022, and the triggers to notify and suspend the warehouse at the specified thresholds. Option A is incorrect because it does not specify the frequency. Option C is incorrect because it does not specify the frequency and it uses notify and suspend instead of suspend and suspend_immediate. Option D is incorrect because it does not specify the start timestamp. For more information about resource monitors, see Working with Resource Monitors and CREATE RESOURCE MONITOR.

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.

According to the Replication considerations documentation, the Time Travel retention period for a secondary database can be different from the primary database. The retention period can be set at the database, schema, or table level using the DATA_RETENTION_TIME_IN_DAYS parameter. Therefore, to extend the Time Travel retention policy to 60 days on the secondary database only, the best option is to set the data retention policy on the secondary database to 60 days using the ALTER DATABASE command. The other options are incorrect because:

•B. Setting the data retention policy on the schemas in the secondary database to 60 days will not affect the database-level retention period, which will remain at 30 days. The most specific setting overrides the more general ones, so the schema-level setting will apply to the tables in the schema, but not to the database itself.

•C. Setting the data retention policy on the primary database to 30 days and the schemas to 60 days will not affect the secondary database, which will have its own retention period. The replication process does not copy the retention period settings from the primary to the secondary database, so they can be configured independently.

•D. Setting the data retention policy on the primary database to 60 days will not affect the secondary database, which will have its own retention period. The replication process does not copy the retention period settings from the primary to the secondary database, so they can be configured independently.

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.

•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.

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.

According to the Network Policies documentation, a network policy can be applied to an account, a security integration, or a user. If there are network policies applied to more than one of these, the most specific network policy overrides more general network policies. The following summarizes the order of precedence:

•Account: Network policies applied to an account are the most general network policies. They are overridden by network policies applied to a security integration or user.

•Security Integration: Network policies applied to a security integration override network policies applied to the account, but are overridden by a network policy applied to a user.

•User: Network policies applied to a user are the most specific network policies. They override both accounts and security integrations.

Therefore, if both the account_level and user_level network policies are defined, the user_level policy will take effect and the account_level policy will be ignored. The other options are incorrect because:

•The account_level policy will not override the user_level policy, as explained above.

•The user_level network policies will be supported, as they are part of the network policy feature.

•A network policy error will not be generated, as there is no conflict between the account_level and user_level network policies.

The inclusion of the CURRENT_TIMESTAMP() function in the second query prevents it from re-using the first query’s persisted result cache because this function makes each execution unique due to the constantly changing timestamp. According to the Snowflake documentation, “The query does not include non-reusable functions, which return different results for successive runs of the same query. UUID_STRING, RANDOM, and RANDSTR are good examples of non-reusable functions.” The CURRENT_TIMESTAMP() function is another example of a non-reusable function, as it returns the current date and time at the start of query execution, which varies for each run. Therefore, the second query is not identical to the first query, and the result cache is not reused. The other options are either incorrect or irrelevant to the question. Option B is incorrect, as the CURRENT_DATE() function is a reusable function, as it returns the same value for all queries executed within the same day. Option C is irrelevant, as the virtual warehouse used to execute the query does not affect the result cache reuse. Option D is also irrelevant, as the role used to execute the query does not affect the result cache reuse, as long as the role has the necessary access privileges for all the tables used in the query.

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 A is a possible solution to address the issues happening once a month, as it allows the administrator to use a task to increase the cluster size for the time period that the more complex queries are running and another task to reduce the size of the cluster once the complex queries complete. This way, the warehouse can have more resources available to handle the complex queries without reaching the maximum limit of 10 clusters, and then return to the normal cluster size to save costs. Option B is another possible solution to address the issues happening once a month, as it allows the administrator to have the group running the complex monthly queries use a separate appropriately-sized warehouse to support their workload. This way, the warehouse can isolate the complex queries from the standard workload and avoid queue time and resource contention. Option C is not a recommended solution to address the issues happening once a month, as it would increase the costs and complexity of managing the multi-cluster warehouse, and may not solve the underlying problem of inefficient queries. Option D is a good practice to improve the performance of the queries, but it is not a direct solution to address the issues happening once a month, as it requires analyzing and optimizing the complex queries using clustering keys or materialized views, which may not be feasible or effective in all cases. Option E is not a recommended solution to address the issues happening once a month, as it would increase the costs and waste resources by starting more clusters than needed for the standard workload.

According to the Snowflake documentation, when a database or schema is cloned, the clone inherits all granted privileges on the clones of all child objects contained in the source object, such as tables and views. However, the clone of the container itself does not inherit the privileges granted on the source container. Therefore, the ANALYST role will have SELECT privilege on all tables and views in DatabaseA_clone.Schema1, but not USAGE privilege on the database or schema. The type of view (secure or non-secure) does not affect the cloning of privileges.

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.

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.

According to the Snowflake documentation1, a standard listing is a type of listing that provides free access to the full data product, with no payment required. A standard listing can be added and queried immediately by the consumer, as long as they accept the terms and conditions of the listing. A monetized listing is a type of listing that charges for access to the data product, using the pricing models offered by Snowflake. A monetized listing requires the consumer to provide payment information and agree to the billing terms before accessing the data product. A regional listing is not a type of listing, but a way to specify the regions where the listing is available. A personalized listing is a type of listing that provides limited trial access to the data product, with unlimited access to the full data product available upon request. A personalized listing requires the consumer to request access from the provider and wait for the provider to grant access before accessing the data product. Therefore, the only type of listing that can be added and queried immediately is the standard listing.

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.

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 command can be executed by the ACCOUNTADMIN role, as well as any role that has been granted the ORGADMIN role1.