You have a Snowflake external stage configured to access Parquet files in an AWS S3 bucket.
You want to query these Parquet files directly using Snowflake without explicitly loading them into a table. You also want to enable directory tables for this external stage. Which of the following steps are necessary to enable directory tables for the external stage and query the data?

• A.Create an external stage pointing to the S3 bucket, then execute 'ALTER STAGE SET ENABLE_DIRECTORY = TRUE;'
• B.Create an external stage pointing to the S3 bucket, then execute 'ALTER STAGE REFRESH;' , then execute 'ALTER STAGE SET ENABLE_DIRECTORY =TRUE;'
• C.Create an external stage pointing to the S3 bucket, execute 'ALTER STAGE SET ENABLE_DIRECTORY = TRUE;' , then refresh the directory table using 'ALTER STAGE REFRESH;'.
• D.Create an external stage pointing to the S3 bucket with 'ENABLE DIRECTORY = TRUE specified during stage creation, then refresh the directory table using 'ALTER STAGE REFRESH;'.
• E.Create an external stage pointing to the S3 bucket with 'ENABLE DIRECTORY = TRUE specified during stage creation, then no refresh is needed. Directory tables are automatically updated.

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Which of the following statements are TRUE regarding Snowflake's data sharing capabilities and its impact on storage costs and data governance? (Select TWO)

• A.Data sharing in Snowflake involves physically copying the data to the consumer's account, resulting in increased storage costs for both the provider and the consumer.
• B.Data sharing in Snowflake allows providers to share live, up-to-date data without physically copying it, resulting in zero storage costs for consumers.
• C.Data providers can revoke access to shared data at any time, ensuring data governance and security.
• D.Consumers can modify the shared data within their Snowflake account without affecting the original data in the provider's account.
• E.Data sharing is only possible between Snowflake accounts within the same cloud region.

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A Snowflake account administrator needs to configure a resource monitor to limit the credit consumption of a specific virtual warehouse named 'ANALYTICS WH'. The resource monitor should trigger a notification when the warehouse consumes 80% of its allocated credits within a calendar month and should suspend the warehouse when it reaches 100%. Which of the following SQL statements, executed in the correct order, would achieve this?

• A.Option A
• B.Option B
• C.Option C
• D.Option D
• E.Option E

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A data engineer needs to grant a group of analysts the ability to query data in the 'SALES DB.PUBLIC.ORDERS table, but prevent them from seeing any personally identifiable information (PII) in the 'CUSTOMER NAME column. Furthermore, the analysts should be able to create temporary tables based on the data. Which of the following steps would BEST accomplish this?

• A.Grant the `SELECT privilege on the 'SALES DB.PUBLIC.ORDERS table to a custom role, then create a view that excludes the 'CUSTOMER NAME' column, granting `SELECT on the view to the role. Grant 'CREATE TEMPORARY TABLE' on the database to the custom role.
• B.Grant the 'SELECT privilege on the 'SALES DB.PUBLIC.ORDERS table and 'CREATE TEMPORARY TABLE' on the database to the PUBLIC role. Use masking policies on the column.
• C.Grant the `SELECT privilege on the 'SALES DB.PUBLIC.ORDERS table to a custom role, create a masking policy to redact the 'CUSTOMER NAME' column, and grant the 'APPLY MASKING POLICY privilege to the custom role. Grant 'CREATE TEMPORARY TABLE on the database to the custom role.
• D.Grant the `SELECT privilege on the 'SALES DB.PUBLIC.ORDERS table to a custom role. Create a secure view that excludes the `CUSTOMER NAME' column, granting `SELECT on the secure view to the role.
  Grant 'CREATE TABLE on the database to the custom role.
• E.Grant the `SELECT privilege on the 'SALES DB.PUBLIC.ORDERS table to a custom role. Create a row access policy to filter data based on user roles. Grant `CREATE TEMPORARY TABLE on the database to the custom role.

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You are designing a data ingestion pipeline for a SaaS application that generates JSON log files daily. These files are uploaded to an AWS S3 bucket. You need to load this data into Snowflake, transform it, and store it in a structured table. Consider the following requirements: 1 . Automated ingestion of new log files as they arrive in S3. 2. Transformation of the JSON data into a relational format. 3. Minimal operational overhead. 4. Cost Optimization. Which combination of Snowflake features would best address these requirements?

• A.Snowpipe with Snowsight Tasks and Materialized Views.
• B.Snowpipe with External Tables and User-Defined Functions (UDFs).
• C.Scheduled Tasks using Cron and Stored Procedures with Python IJDF.
• D.Snowpipe with Streams and Tasks.
• E.Snowpipe with COPY INTO and Views.

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