ADA-C01 Exam Dumps - Snowflake Certification Questions and Answers

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 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.

The EXPLAIN command returns the logical execution plan for a query, which shows the upper bound estimates for the number of partitions and bytes that might be scanned by the query1. However, these estimates do not account for the runtime optimizations that Snowflake performs to improve the query performance and reduce the resource consumption2. One of these optimizations is join pruning, which eliminates unnecessary partitions from the join inputs based on the join predicates2. This can result in fewer partitions and bytes scanned than the estimates from the EXPLAIN output3. Therefore, the actual partitions scanned value in the Query Profile can be lower than the partitionsAssigned value in the EXPLAIN output4.

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, network policies are a feature that allows restricting access to your account based on user IP address. A network policy can be applied to an account, a user, or a security integration, and can specify a list of allowed IP addresses and a list of blocked IP addresses. If there are network policies applied to more than one of these, the most specific network policy overrides more general network policies. In this case, the user1 has a network policy (bar_policy) applied to them, which overrides the account-level network policy (foo_policy). The bar_policy allows access only from the IP range 3.3.3.0/24, and blocks access from the IP address 3.3.3.10. Therefore, the user1 will not be able to log in to Snowflake from IP address 3.3.3.10, as it is found in the BLOCKED_IP_LIST of bar_policy. Option A is incorrect because the ALLOWED_IP_LIST of bar_policy does not override the BLOCKED_IP_LIST of bar_policy. Option C is incorrect because the ALLOWED_IP_LIST of foo_policy does not apply to user1, as it is overridden by the user-level network policy. Option D is incorrect because the ALLOWED_IP_LIST of foo_policy does not matter, as it is overridden by the user-level network policy.

According to the Snowflake documentation1, Snowflake supports SCIM 2.0 to integrate Snowflake with Okta and Microsoft Azure AD, which both function as identity providers. Snowflake also supports identity providers that are neither Okta nor Microsoft Azure (i.e. Custom). Therefore, the SCIM integration types that are supported in Snowflake are Okta, Custom, and Azure AD. Option A is incorrect because Amazon Web Services (AWS) is not a SCIM identity provider. Option B is incorrect because Google Cloud Platform (GCP) is not a SCIM identity provider. Option F is incorrect because Duo Security Provisioning Connector is not a SCIM identity provider.

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 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.

Network policies are used to restrict access to the Snowflake service and internal stages based on user IP address1. To create network policies, a role must have the global permission of CREATE NETWORK POLICY2. By default, the system-defined roles of SECURITYADMIN and ACCOUNTADMIN have this permission3. However, any other role can be granted this permission by an administrator4. Therefore, the answer is B, C, and E. The other options are incorrect because SYSADMIN and ORGADMIN do not have the CREATE NETWORK POLICY permission by default3, and network policies are not tied to specific databases5.

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.