DEA-C01 Question 452
Single answerA financial organization processes large volumes of transactional data daily. They require near real-time analytics to detect fraudulent transactions and need a solution that provides low-latency streaming, scalability, and integration with their existing AWS data lake built on Amazon S3. Which AWS service would be the most suitable for ingesting and processing this streaming data?
- A
Amazon Kinesis Data Streams
- B
Amazon SQS
- C
AWS Glue
- D
Amazon Redshift
Show answer and explanation
Correct answer: A
Explanation
Amazon Kinesis Data Streams is the most appropriate service for ingesting and processing streaming data in real time. It provides low-latency capabilities that are essential for detecting fraud in transactional data. Additionally, its scalability and integration with data lakes, such as those built on Amazon S3, make it ideal for this scenario.
- A. Correct.
Amazon Kinesis Data Streams is designed for real-time data streaming and processing, making it suitable for use cases like fraud detection with low-latency requirements. It can integrate with other AWS services, such as S3, for seamless data flows.
- B. Incorrect.
Amazon SQS is a message queuing service, which is ideal for decoupling distributed systems but is not tailored for real-time streaming and analytics.
- C. Incorrect.
AWS Glue is primarily a data integration service for ETL (Extract, Transform, Load) processes and is not optimized for handling real-time streaming data.
- D. Incorrect.
Amazon Redshift is a data warehousing service designed for analytics on structured data but is not intended for ingesting or processing real-time streaming data.