Answer-first summary for fast verification
Answer: Use AWS Lambda to process the data and Amazon Athena to query it for verification.
To verify the integrity and quality of a dataset, AWS Lambda can be used to run custom code for data validation and cleaning. This can include checks for missing values, data type consistency, and other quality issues. Amazon Athena can then be used to query the cleaned data, ensuring that it is ready for analysis. This approach allows for flexible and scalable data verification and cleaning.
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You need to verify the integrity and quality of a dataset stored in S3 before performing any analysis. Which AWS services would you use to perform this verification, and what specific steps would you take to ensure the data is clean and ready for analysis?
A
Use AWS Glue to transform the data and Amazon Athena to query it for verification.
B
Use Amazon SageMaker Data Wrangler to clean the data and Amazon QuickSight to visualize it for verification.
C
Use AWS Lambda to process the data and Amazon Athena to query it for verification.
D
Use Amazon S3 Select to filter the data and Amazon Athena to query it for verification.
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