MLA-C01 · Question #176
A company collects customer data every day. The company stores the data as compressed files in an Amazon S3 bucket that is partitioned by date. Every month, analysts download the data, process the…
The correct answer is A. Run an AWS Glue crawler every month to update the AWS Glue Data Catalog. Use AWS Glue. AWS Glue Data Quality provides a managed, rules-based way to automatically evaluate data quality with minimal custom code. Running a Glue crawler updates the Data Catalog so the partitioned S3 data is discoverable and can be assessed consistently before being used for…
Question
A company collects customer data every day. The company stores the data as compressed files in an Amazon S3 bucket that is partitioned by date. Every month, analysts download the data, process the data to check the data quality, and then upload the data to Amazon QuickSight dashboards. An ML engineer needs to implement a solution to automatically check the data quality before the data is sent to QuickSight. Which solution will meet these requirements with the LEAST operational overhead?
Options
- ARun an AWS Glue crawler every month to update the AWS Glue Data Catalog. Use AWS Glue
- BUse an AWS Glue trigger to run an AWS Glue crawler every month to update the AWS Glue Data
- CRun Python scripts on an AWS Lambda function every month to evaluate data quality. Configure
- DConfigure the S3 bucket to send event notifications to an Amazon Simple Queue Service
How the community answered
(27 responses)- A74% (20)
- B15% (4)
- C7% (2)
- D4% (1)
Explanation
AWS Glue Data Quality provides a managed, rules-based way to automatically evaluate data quality with minimal custom code. Running a Glue crawler updates the Data Catalog so the partitioned S3 data is discoverable and can be assessed consistently before being used for downstream analytics in QuickSight.
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