Snowflake ADA-C01 Exam With Confidence Using Practice Dumps

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 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 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.