Most Recent Snowflake ADA-C01 Exam Questions & Answers

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.

Snowflake charges for database replication based on two categories: data transfer and compute resources1. Data transfer costs depend on the amount of data that is transferred from the primary database to the secondary database across regions and/or cloud service providers2. Compute resource costs depend on the use of Snowflake-provided compute resources to copy data between accounts across regions1. Both data transfer and compute resource costs are proportional to the frequency and amount of changes to the primary database as a result of data loading or DML operations3. Therefore, the answer is A and B. The other options are not directly related to the replication billing, as the frequency of secondary database refreshes does not affect the amount of data transferred or copied4, and the number and size of warehouses defined in the primary account do not affect the replication process5.

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.

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 documentation1, clustering keys are most effective when the data is evenly distributed across the key values. If the data is skewed, such as in this case where most sales come from only 20 stores out of 1000, then the micro-partitions will not be well-clustered and the pruning will be poor. This means that more bytes will be scanned by queries, even if they filter by STORE_ID. Option A is incorrect because the data type of the clustering key does not affect the pruning. Option B is incorrect because the table is large enough to benefit from clustering, if the data was more balanced. Option D is incorrect because the cardinality of the clustering key is not relevant for pruning, as long as the key values are distinct.

1: Considerations for Choosing Clustering for a Table | Snowflake Documentation