Get AI-ready data from the edge
Many organizations recognize the growing importance of data in motion as a foundation for real-time AI and the next generation of intelligent applications. However, the path to effectively implementing edge to AI strategies is often unclear. This guide offers a practical roadmap to transforming data from edge devices into real-time AI use cases, along with best practices, implementation tips, tactical insights on common architectures, tooling options, and tradeoffs.
You will learn how to:
Identify AI edge use cases
Integrate data in motion architecture
Apply data governance to the entire data lifecycle
