MLS-C01 Question 18
Select 2A data science team is tasked with building a machine learning pipeline to analyze streaming data generated by IoT sensors deployed across multiple locations. The team needs to ingest this data into a data lake for further processing and analysis. The pipeline should handle high-throughput, low-latency data streams and ensure data durability. Which AWS services should the team use to implement the data ingestion solution?
- A
Amazon Kinesis Data Streams for ingesting the streaming data and Amazon S3 for storing the data in the data lake
- B
Amazon RDS for real-time ingestion and storage of the streaming data
- C
AWS Glue for ingesting the streaming data and processing it for the data lake
- D
Amazon Kinesis Data Firehose for transforming and loading the streaming data into Amazon S3
- E
Amazon DynamoDB Streams for ingesting the IoT data and storing it in DynamoDB
Show answer and explanation
Correct answers: A, D
Explanation
To ingest high-throughput, low-latency streaming data generated by IoT sensors, the team should use Amazon Kinesis Data Streams or Amazon Kinesis Data Firehose. Kinesis Data Streams allows for real-time data ingestion and processing, while Kinesis Data Firehose provides an easier way to transform and load the data into Amazon S3 for storage in the data lake. Both services are suited for handling streaming data ingestion and ensure durability and scalability. Other options like Amazon RDS, AWS Glue, or DynamoDB Streams are not designed for this use case.
- A. Correct.
Correct: Amazon Kinesis Data Streams is designed for ingesting and processing high-throughput, low-latency streaming data. Paired with Amazon S3, it ensures the data can be durably stored in a data lake for further analysis.
- B. Incorrect.
Incorrect: Amazon RDS is designed for relational database storage, not high-throughput streaming data ingestion. It is not suitable for handling real-time IoT data ingestion.
- C. Incorrect.
Incorrect: AWS Glue is primarily used for ETL (Extract, Transform, Load) operations and data preparation, not for real-time data ingestion. It is not designed to handle high-throughput streaming data.
- D. Correct.
Correct: Amazon Kinesis Data Firehose is a fully managed service that allows you to transform and load streaming data into Amazon S3 with minimal effort. It is ideal for building data pipelines for a data lake.
- E. Incorrect.
Incorrect: Amazon DynamoDB Streams is used for capturing and processing change data in DynamoDB tables, but it is not designed for high-throughput streaming data ingestion from external sources like IoT sensors.