AWS IoT Analytics
In Chapter 9, we leveraged AWS IoT and the AWS edge or AWS SDK to send data to the cloud. Once the devices are connected and the time-series data is sent to the cloud, IIoT data should be analyzed, processed, and visualized. AWS provides six different mechanisms to process data:
- Serverless Lambda functions
- Greengrass, which can be used to deploy Lambda functions on-premises
- IoT Analytics
- Athena
- SageMaker
SageMaker and Athena
AWS SageMaker is a general-purpose machine learning and deep learning framework used to develop advanced analytics. SageMaker works very well with S3, so we need to create a batch to export data continuously from Timestream to S3. This operation is very easy to configure using AWS Data Pipeline. AWS Athena is a powerful SQL query language for business intelligence that is easy to apply to NoSQL’s context.
IoT Analytics
IoT Analytics is another analytical framework for IoT data transformation and enrichment...
