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Google Professional Data Engineer

Google Professional Data Engineer

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You are developing an Extract, Load, Transform (ELT) solution using Dataform in Google BigQuery. As part of the data quality assurance process, it is crucial to ensure the uniqueness and the absence of null values in your final dataset tables. How can you efficiently incorporate these checks within your ELT pipeline?

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Explanation:

The correct answer is C. Dataform provides a feature called 'assertions,' which are SQL-based tests you can define to verify the quality of your data. Assertions in Dataform are a built-in way to perform data quality checks, including checking for uniqueness and null values in your tables. This makes it efficient and seamless to integrate these checks into your ELT pipeline.

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