DOP-C02 · Question #132
A company is storing 100 GB of log data in .csv format in an Amazon S3 bucket. SQL developers want to query this data and generate graphs to visualize it. The SQL developers also need an efficient, au
The correct answer is B. Filter the data through Amazon QuickSight to visualize the data. C. Query the data with Amazon Athena. E. Use the AWS Glue Data Catalog as the persistent metadata store.. https://docs.aws.amazon.com/glue/latest/dg/catalog-and-crawler.html
Question
A company is storing 100 GB of log data in .csv format in an Amazon S3 bucket. SQL developers want to query this data and generate graphs to visualize it. The SQL developers also need an efficient, automated way to store metadata from the .csv file. Which combination of steps will meet these requirements with the LEAST amount of effort? (Choose three.)
Options
- AFilter the data through AWS X-Ray to visualize the data.
- BFilter the data through Amazon QuickSight to visualize the data.
- CQuery the data with Amazon Athena.
- DQuery the data with Amazon Redshift.
- EUse the AWS Glue Data Catalog as the persistent metadata store.
- FUse Amazon DynamoDB as the persistent metadata store.
How the community answered
(46 responses)- A9% (4)
- B83% (38)
- D7% (3)
- F2% (1)
Explanation
https://docs.aws.amazon.com/glue/latest/dg/catalog-and-crawler.html
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