AWS Certified Data Engineer Associate · Free Practice Question Medium
Question 47
A retail company uses AWS Glue DataBrew to clean and prepare customer data for analytics. The data is stored in various formats, including CSV and JSON, in Amazon S3. The company wants to ensure consistent formatting across the datasets by removing null values, standardizing column names, and converting dates into a uniform format. What is the best approach to achieve this with AWS Glue DataBrew?
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A
Use Glue Data Catalog to create new metadata definitions
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B
Use AWS Glue ETL Jobs to perform data transformations
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C
Use DataBrew Recipes to apply transformation steps
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D
Use Glue Crawlers to infer the schema of the data
Reveal correct answer
Correct answer: C
A.
The Glue Data Catalog stores metadata, but it does not directly perform data transformation or cleaning tasks.
B.
AWS Glue ETL Jobs can perform transformations, but DataBrew is more user-friendly for this task, especially for users without coding expertise.
C.
AWS Glue DataBrew Recipes provide a no-code interface that allows users to apply a series of transformation steps, such as removing null values, renaming columns, and standardizing date formats, to clean and prepare data for analytics.
D.
Glue Crawlers are used to infer schema but are not used for cleaning or transforming data.
Discussion
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