DAA-C01 Exam Dumps | You're developing a data quality process in Snowflake that relies on identifying duplicate records within

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Question 85/151

You're developing a data quality process in Snowflake that relies on identifying duplicate records within a large table named 'TRANSACTIONS. You need to generate a hash value for each row based on several key columns ('transaction_id', 'customer_id' , amount', to efficiently compare rows and detect duplicates. However, some of these columns may contain NULL values, which you want to handle consistently during the hash generation. Which of the following approaches, utilizing Snowflake's system functions, will MOST reliably generate a consistent hash value for duplicate rows, even when some of the key columns contain NULLs? (Select TWO)

A. Use the customer_id, amount, transaction_date)' function directly, as Snowflake automatically handles NULLs in hashing functions.

B. Use the 'SHA2(CONCAT(NVL(transaction_id, 'I), NVL(customer_id, "), NVL(amount, "), NVL(transaction_date, "))) function, replacing NULLs with empty strings using the NVL function before concatenation.

C. Use the II customer_id II amount II transaction_date)' function. Snowflake implicitly converts NULL to a default value during string concatenation.

D. Use the WS('I', transaction_id, customer_id, amount, function. This concatenates strings with a separator, handling NULLs implicitly by skipping them in concatenation, leading to inconsistencies.

E. Use the AS VARCHAR), AS VARCHAR), AS VARCHAR), NVL(CAST(transaction_date AS VARCHAR), function, explicitly converting each value to a string and replacing NULLs with empty strings using NVL.

Question 85/151

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