AWS Certified Solutions Architect – Associate (SAA-C02) — Question 705

A company is preparing a new data platform that will ingest real-time streaming data from multiple sources. The company needs to transform the data before writing the data to Amazon S3. The company needs the ability to use SQL to query the transformed data.
Which solutions will meet these requirements? (Choose two.)

Answer options

• A. Use Amazon Kinesis Data Streams to stream the data. Use Amazon Kinesis Data Analytics to transform the data. Use Amazon Kinesis Data Firehose to write the data to Amazon S3. Use Amazon Athena to query the transformed data from Amazon S3.
• B. Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to stream the data. Use AWS Glue to transform the data and to write the data to Amazon S3. Use Amazon Athena to query the transformed data from Amazon S3.
• C. Use AWS Database Migration Service (AWS DMS) to ingest the data. Use Amazon EMR to transform the data and to write the data to Amazon S3. Use Amazon Athena to query the transformed data from Amazon S3.
• D. Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to stream the data. Use Amazon Kinesis Data Analytics to transform the data and to write the data to Amazon S3. Use the Amazon RDS query editor to query the transformed data from Amazon S3.
• E. Use Amazon Kinesis Data Streams to stream the data. Use AWS Glue to transform the data. Use Amazon Kinesis Data Firehose to write the data to Amazon S3. Use the Amazon RDS query editor to query the transformed data from Amazon S3.

Correct answer: A, B

Explanation

Options A and B are correct because they offer viable architectures for ingestion (Amazon Kinesis Data Streams or Amazon MSK), transformation (Kinesis Data Analytics or AWS Glue), and querying S3 data with SQL via Amazon Athena. Option C is incorrect because AWS DMS is not designed for ingesting real-time streaming data from multiple sources. Options D and E are incorrect because the Amazon RDS query editor is used to query databases in RDS, not files stored in Amazon S3.