DEA-C01 Question 44
Single answerA company is processing large volumes of sensor data in real time. They need to perform transformations, such as filtering irrelevant data and aggregating metrics, before storing the results in an Amazon Redshift data warehouse for further analysis. Which AWS service is best suited to handle the transformation and processing of this streaming data in real time?
- A
AWS Glue
- B
Amazon Kinesis Data Analytics
- C
Amazon EMR
- D
AWS Batch
Show answer and explanation
Correct answer: B
Explanation
Amazon Kinesis Data Analytics is the best choice for real-time data transformations as it is built specifically for processing streaming data. It integrates seamlessly with Amazon Kinesis streams to ingest real-time data, perform necessary transformations (like filtering and aggregations), and output the processed data to downstream systems such as Amazon Redshift. While other services like AWS Glue and Amazon EMR are powerful, they are not optimized for real-time streaming workflows.
- A. Incorrect.
AWS Glue is primarily used for ETL (Extract, Transform, Load) tasks on batch data, not for real-time streaming data transformations.
- B. Correct.
Amazon Kinesis Data Analytics is specifically designed to process streaming data in real time, allowing for transformations such as filtering, aggregations, and other operations.
- C. Incorrect.
Amazon EMR is used for big data processing using frameworks like Apache Spark or Hadoop but is typically suited for batch processing rather than real-time streaming data transformation.
- D. Incorrect.
AWS Batch is used for running batch workloads and is not designed for real-time data processing and transformation.