DEA-C01 Question 47
Select 1You are a data engineer working on a data pipeline that processes large volumes of unstructured data from IoT devices. The data needs to be ingested in near real-time, stored, and later queried for analytics. Which combination of AWS services would be the most appropriate to fulfill this requirement?
- A
Amazon Kinesis Data Streams for ingestion, Amazon S3 for storage, and Amazon Athena for querying
- B
Amazon SQS for ingestion, Amazon RDS for storage, and Amazon Redshift for querying
- C
Amazon Kinesis Firehose for ingestion, Amazon DynamoDB for storage, and Amazon QuickSight for querying
- D
Amazon Kafka for ingestion, Amazon EFS for storage, and Amazon EMR for querying
Show answer and explanation
Correct answer: A
Explanation
To process large volumes of unstructured data from IoT devices in near real-time, Amazon Kinesis Data Streams is an excellent choice for ingestion as it supports high-throughput, low-latency streaming. Amazon S3 is a cost-effective and highly scalable storage solution for unstructured data, and Amazon Athena allows you to query data stored in S3 using standard SQL without managing any infrastructure. This combination effectively meets the requirements of the scenario.
- A. Correct.
This is the correct answer. Amazon Kinesis Data Streams can handle near real-time ingestion of streaming data, Amazon S3 provides a scalable and durable storage solution for unstructured data, and Amazon Athena enables serverless querying of data stored in S3.
- B. Incorrect.
This is incorrect. Amazon SQS is more suitable for asynchronous message queuing, not real-time ingestion. Amazon RDS is not optimized for handling large volumes of unstructured data, and Amazon Redshift is better suited for structured data in a data warehouse.
- C. Incorrect.
This is incorrect. While Amazon Kinesis Firehose can ingest data, Amazon DynamoDB is not designed for storing large volumes of unstructured data. Additionally, Amazon QuickSight is a BI tool, not a querying service for raw data.
- D. Incorrect.
This is incorrect. Amazon Kafka is a valid alternative for streaming ingestion, but Amazon EFS is not ideal for storing large-scale unstructured data. Also, Amazon EMR is typically used for processing and not for querying directly.