DAA-C01 Exam Dumps | You are tasked with enriching a customer dataset in Snowflake. The 'CUSTOMER DATA table contains customer

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Question 108/151

You are tasked with enriching a customer dataset in Snowflake. The 'CUSTOMER DATA table contains customer IDs and country codes. You have a separate 'COUNTRY INFORMATION' table that contains country codes and corresponding currency codes. Both tables reside in the 'RAW DATA schema of the 'ANALYTICS DB' database. You need to create a view called ENRICHED CUSTOMER DATA' in the 'TRANSFORMED DATA' schema that joins these tables to add currency information to the customer data'. You want to optimize this view for performance. Which of the following approaches would be the MOST efficient and scalable, considering potential data volume increases?

A. Create a materialized view using a simple JOIN between 'CUSTOMER_DATA' and 'COUNTRY_INFORMATION'.

B. Create a standard view using a JOIN between 'CUSTOMER DATA' and 'COUNTRY INFORMATION'. Refresh the view regularly using a scheduled task.

C. Use a User-Defined Function (UDF) to look up the currency code from the "COUNTRY_INFORMATION' table based on the customer's country code.

D. Create a secure view joining the two tables and granting access to users.

E. creates a materialized view with clustering enabled on the 'COUNTRY_CODE column after joining 'CUSTOMER_DATX and 'COUNTRY_INFORMATION'.

Correct Answer: E

Materialized views generally provide better performance than standard views for complex queries, especially with joins. Clustering on the 'COUNTRY_CODE column further enhances performance by physically organizing the data based on this column, making lookups more efficient. Using secure view wouldn't impact on performance. Regular view refreshment using scheduled task is not as efficient compared to materialized view. UDFs can introduce performance overhead, especially for large datasets.

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