A manufacturing company has structured and unstructured data stored in an Amazon S3 bucket A Machine Learning Specialist wants to use SQL to run queries on this data.
Which solution requires the LEAST effort to be able to query this data?
A . Use AWS Data Pipeline to transform the data and Amazon RDS to run queries.
B . Use AWS Glue to catalogue the data and Amazon Athena to run queries
C . Use AWS Batch to run ETL on the data and Amazon Aurora to run the quenes
D . Use AWS Lambda to transform the data and Amazon Kinesis Data Analytics to run queries
Answer: B
Explanation:
AWS Glue is a serverless data integration service that can catalogue, clean, enrich, and move data between various data stores. Amazon Athena is an interactive query service that can run SQL queries on data stored in Amazon S3. By using AWS Glue to catalogue the data and Amazon Athena to run queries, the Machine Learning Specialist can leverage the existing data in Amazon S3 without any additional data transformation or loading. This solution requires the least effort compared to the other options, which involve more complex and costly data processing and storage services.
Reference: AWS Glue, Amazon Athena
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