DEA-C01 Question 421
Select 2A company is processing a large volume of streaming data from IoT devices using Amazon Kinesis Data Streams. The data needs to be stored in a data lake on Amazon S3 for long-term analysis. The company also requires the data to be transformed and enriched before storage. Which combination of services should you use to achieve this in a cost-effective and scalable manner?
- A
Use AWS Lambda to process and transform data from Kinesis Data Streams and store it directly in Amazon S3.
- B
Use Amazon Kinesis Data Firehose to automatically transform, enrich, and deliver the data to Amazon S3.
- C
Use Amazon EMR to process the data from Kinesis Data Streams and store it in Amazon S3.
- D
Use AWS Glue to extract, transform, and load (ETL) the data from Kinesis Data Streams to Amazon S3.
- E
Use Amazon Redshift to process the data from Kinesis Data Streams and export it to Amazon S3.
Show answer and explanation
Correct answers: B, C
Explanation
For processing and transforming streaming data from Amazon Kinesis Data Streams in a cost-effective and scalable manner, Amazon Kinesis Data Firehose and Amazon EMR are the most suitable options. Kinesis Data Firehose provides built-in capabilities for automatic transformation and delivery to Amazon S3, while Amazon EMR offers the flexibility to handle more complex transformations and large-scale processing requirements. AWS Lambda and AWS Glue are not optimal for large-scale streaming use cases, and Amazon Redshift is not suitable for real-time data processing.
- A. Incorrect.
AWS Lambda can be used for lightweight transformations, but it is not designed for large-scale, continuous data processing. It is also less cost-effective for high-throughput data streams.
- B. Correct.
Amazon Kinesis Data Firehose is a fully managed service that can automatically transform, enrich, and deliver streaming data to Amazon S3, making it cost-effective and scalable.
- C. Correct.
Amazon EMR is a scalable solution for processing large volumes of data from Kinesis Data Streams. It can efficiently handle complex transformations and store the processed data in Amazon S3.
- D. Incorrect.
AWS Glue is primarily designed for batch ETL operations, not for real-time data streaming from Kinesis Data Streams.
- E. Incorrect.
Amazon Redshift is a data warehouse and not intended for real-time data processing or transformation. It is better suited for querying and analyzing structured data.