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Microsoft and TIBCO Team Up to Bring Machine Learning and AI to IoT and the Edge

Blog: The Tibco Blog

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In our continuing commitment to accelerate digital business transformation through the use of artificial intelligence (AI) and machine learning (ML), TIBCO unveiled the capabilities of TIBCO Spotfire® and TIBCO® Data Science to support Microsoft Azure Cognitive Services at a recent  Build conference. Thanks to this combo of TIBCO and Microsoft technologies, sensor data, and log data can now be analyzed on edge devices with little to no internet connectivity. This means less lag time for analytics and hence, faster response times for businesses based on that intelligence, particularly in places with unreliable internet connections. 

The need for intelligence at the edge without internet connectivity is growing fast. In fact, in a report by Gartner, they predict that “By 2022, more than 50% of enterprise-generated data will be created and processed outside the data center or cloud.” As more devices become intelligent, there will be a greater need for processing the data they collect outside of core systems and closer to the edge. 

Think of factory floors, shipping containers at sea, and any other location where the internet is spotty. Now, in places with little to no internet connectivity, developers can bring the power of TIBCO visual analytics and data science solutions to detect and prevent anomalies. Anomalies help improve their organization’s operational efficiency and lower equipment costs.

“Increasingly, customers performing predictive maintenance must look for ways to leverage AI closer to where their data is generated for timely analytics and responses,” said Matt Quinn, Chief Operating Officer, TIBCO. So, for those who have focused on bringing AI to their core systems, it’s now time to think about how you can extend intelligence to your Internet of Things (IoT) and edge devices that might lack full-time internet connectivity.

For those who have focused on bringing AI to their core systems, it’s now time to think about how you can extend intelligence to your Internet of Things (IoT) and edge devices that might lack full-time internet connectivity.
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Some excellent use cases highlighting the power of intelligence at the edge where internet connectivity is questionable or shaky have been popping up in recent years including the University of Iowa Hospitals and Clinics who are proactively predicting infection rates using advanced analytics on data collected on medical devices. Their efforts saw a drop of 74 percent in onsite surgical infections as a result of making predictive decisions directly in operating rooms. Anadarko, an oil and gas exploration and production company that has been working with TIBCO for several years, increased the speed of their drilling projects by 10 times even though many of their drill sites are in the middle of the ocean or in underdeveloped countries where internet connectivity is spotty at best. 

With so much data being generated at the edge, it’s not always practical to bring that data back to a central location for processing. You need the capabilities of AI and ML to bring better and faster decisioning to the edge without the limitations of, slow or no internet connectivity. For more information on how the TIBCO plus Microsoft use case might be able to help your company realize machine learning at the edge, please visit Microsoft Channel 9 for the demo given at the Build Conference, read the TechTarget News article or TIBCO press release for more details.

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