Implementing Data Engineering Solutions Using Microsoft Fabric — Question 44

You have a Fabric warehouse named DW1 that contains a Type 2 slowly changing dimension (SCD) dimension table named DimCustomer. DimCustomer contains 100 columns and 20 million rows. The columns are of various data types, including int, varchar, date, and varbinary.

You need to identify incoming changes to the table and update the records when there is a change. The solution must minimize resource consumption.

What should you use to identify changes to attributes?

Answer options

• A. a hash function to compare the attributes in the source table.
• B. a direct attributes comparison across the attributes in the DimCustomer table.
• C. a direct attributes comparison for the attributes in the source table.
• D. a hash function to compare the attributes in the DimCustomer table.

Correct answer: A

Explanation

Using a hash function to compare the attributes in the source table (option A) is efficient because it reduces the amount of data processed by only requiring the computation of hash values instead of comparing each attribute directly. The other options involve direct comparisons, which can be resource-intensive and less efficient, especially with a large dataset of 20 million rows.