Industrial IOT applications must be ready to receive and react to streaming data from sensors in real time. Unfortunately most organizations are unprepared to process the deluge of time-critical data in real-time. Networks get swamped, storage requirements are huge, and application processing needs are growing every day. Few organizations are ready to trust their critical Operational Technology (OT) applications and data to third party cloud providers. Organizations must deal with data at the source, to turn floods of data into manageable streams.
Here are the five big questions you should be asking about IOT and the transformation of OT into Intelligent IOT:
Five Big Questions about IOT
- Is it an IT (Information Technology) or OT (Operational Technology) Problem?
- What Do I Do with All This Data?
- How Do I Keep All This Data Secure?
- Can I Enrich My Data Set?
- Why Is Speed Important?
Streaming data contains hidden patterns that are processed and discovered using machine learning algorithms. Industrial data can be highly time-critical. Oftentimes, it is already too late to address real-time operational issues due to latency of batch analysis of data. By applying machine learning at the edge, results of stream analysis can inform business applications in real-time. With easily accessible, high-level context, and data insights decisions can now be made quickly, by operators or even automatically, thereby enabling IIOT applications to prevent issues before they occur.
Learn more about how Swim is able to help you gain actionable, business insights from your Industrial IOT data.