You work for a city government in their shared bike program as a machine learning specialist. You need to visualize the bike share location predictions you are producing on an hourly basis using your model inference you created using the SageMaker built-in K-Means algorithm. Your inference endpoint takes IoT data from your shared bikes as they are used throughout the city. You also want to enrich your shared bike data with external data sources such as current weather and road conditions.
Which set of Amazon services would you use to create your visualization with the least amount of effort?

Answer options:

A.IoT Core -> IoT Analytics ->SageMaker -> QuickSight
B.IoT Core -> Kinesis Firehose -> SageMaker -> QuickSight
C.IoT Core -> Lambda -> SageMaker -> QuickSight
D.IoT Core -> IoT Greengrass -> QuickSight

Answer: A
Option A is correct. IoT Core collects data from each shared bike, IoT Analytics retrieves messages from the shared bikes as they stream data, IoT Analytics also enriches the streaming data with your external data sources and sends the streaming data to your K-Means machine learning inference endpoint, QuickSight is then used to create your visualization. This approach requires the least amount of effort mainly because of the data enrichment feature of IoT Analytics.
Option B is incorrect. With this option, you would have to create a lambda function to gather the data enrichment information (weather, road conditions) and enrich the data streams in your own code.
Option C is incorrect. Also, with this option, you would have to add code to your lambda function to gather the data enrichment information (weather, road conditions) and enrich the data streams in your own code.
Option D is incorrect. IoT Greengrass is a service that you use to run local machine learning inference capabilities on connected devices. This approach would not easily integrate with your QuickSight visualization. 
Reference:
Please see the AWS IoT Analytics overview, the Amazon SageMaker developer guide titled K-Means Algorithm, the AWS Big Data blog titled Build a Visualization and Monitoring Dashboard for IoT Data with Amazon Kinesis Analytics and Amazon QuickSight, the AWS IoT Analytics User Guide titled What IS AWS IoT Analytics?, and the AWS IoT Greengrass FAQs.