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Answer: Utilize Amazon Kinesis Data Streams for data ingestion, Amazon Kinesis Data Analytics for transformation, Amazon Kinesis Data Firehose for data storage in S3, and Amazon Athena for SQL querying., Employ Amazon MSK for data streaming, AWS Glue for data transformation and storage in S3, and Amazon Athena for querying the stored data.
Option A is correct because it uses Amazon Kinesis Data Streams for streaming, Amazon Kinesis Data Analytics for data transformation, and Amazon Kinesis Data Firehose for loading data into Amazon S3, with Amazon Athena used to query the transformed data. Option B is also correct as it uses Amazon MSK for streaming, AWS Glue for data transformation and loading into S3, and Amazon Athena for querying the data. Both A and B satisfy the requirements of real-time data ingestion, transformation, storage in Amazon S3, and the ability to query using SQL.
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A company requires a data platform for real-time streaming data ingestion, transformation, storage in Amazon S3, and SQL query capability on the transformed data. Identify two compatible solutions.
A
Utilize Amazon Kinesis Data Streams for data ingestion, Amazon Kinesis Data Analytics for transformation, Amazon Kinesis Data Firehose for data storage in S3, and Amazon Athena for SQL querying.
B
Employ Amazon MSK for data streaming, AWS Glue for data transformation and storage in S3, and Amazon Athena for querying the stored data.
C
Adopt AWS DMS for initial data ingestion, Amazon EMR for data transformation and S3 storage, and Amazon Athena for querying the transformed data.
D
Leverage Amazon MSK for streaming, Amazon Kinesis Data Analytics for transformation and S3 storage, and the Amazon RDS query editor for data querying.