The IoT analytical life cycle expands traditional analysis processing beyond investigation of stored data (i.e., at rest) to analytical investigation of streaming data (i.e., in motion) or at the edge. The combined capability of data management, streaming analytics execution, and intelligent decisioning enables fast and confident decision making from data, to discovery, to deployment.
SAS Analytics for IoT offers an optimized IoT solution ecosystem and addresses the entire analytical life cycle.
In this document we are focusing on the integrated process of model management and analytics deployment.
- Learn how to import ASTORE from models built in SAS Model Studio, SAS Studio, or Jupyter Notebook into SAS Model Manager
- Learn how to deploy ASTORE from SAS Model Manager in SAS Event Stream Processing Studio
This repo is not open for external contributions.
This project is licensed under the Apache 2.0 License.
- General information about SAS Analytics for IoT
- An overview of SAS Model Manager
- An overview of SAS Event Stream Processing
- SAS Support Communities website
- You can find additional IoT use cases on the SAS for Developers website
- SAS Event Stream Processing Free Trial