The power of fog computing is its ability to let enterprises make mission-critical decisions faster and closer to the edge. A sensor network is only as valuable as the intelligence that can be gleaned and strategic analytics is the path to that value.
Predixion Software, a developer of cloud-based advanced analytics software, announced on May 12 its Predixion Insight 4.5. This new software enables analytic models to run directly within the cloud, at the gateway and on devices, so organizations can perform real-time analytics and automated actions at the edge. This enables more nimble operations and efficient decision-making.
“The value of IoT-connected machines will only be realized if organizations can understand and leverage the data they produce,” said Jamie MacLennan, CTO, Predixion Software. “Predixion 4.5 allows users to create value from the data generated from the IoT by efficiently deploying advanced analytics in any modality to improve operations, reduce costs, enable richer customer experiences, and improve patient care.”
Predixion Insight’s patent-pending Machine Learning Semantic Model (MLSM) technology makes it ideal for IoT analytics solutions. It provides flexibility in predictive placements, or the ability for advanced analytic packages to be embedded directly into a variety of production environments. Unlike traditional analytics tools which can struggle with analyzing streaming data after it’s collected, Predixion Insight analyzes live data on the edge.
“What Predixion has done to simplify the deployment of advanced analytic models into production environments is outstanding. But the ability to enable on-device deployment is a real game-changer,” said Oliver Downs, Chief Scientist at big data analytics company Globys. “Getting advanced analytics on the edge to take action is the ultimate payoff of big data and the Internet of Things, and Predixion makes that possible.”
In addition to the MLSM at the heart of the tech, Predixion Insight 4.5 delivers several new capabilities. It can quickly deploy predictive analytics by generating source code and facilitating deployment of the MLSM package to devices, gateway or cloud. While being faster, it also achieves greater accuracy with new algorithms optimized for IoT use cases and eases collaboration across teams by sharing models and results over the Web, email, and social media.
The IoT needs the fog to make data clear at the edge. Get it?
Edited by
Dominick Sorrentino
