Decisyon, maker of Decisyon 360, a platform for building intelligent IoT solutions, announced its new version of the analytics manager on April 28. The company's flagship platform deepens support for big data, IoT real-time analytics and process methodologies.
Key features of the new distribution include: Complex event processing to extract and process real-time intelligence and patterns from data respond immediately; advanced business rules management for big data to define, deploy, execute, monitor and maintain the variety and complexity of decisions, allowing businesses to streamline operations, lower cost and minimize time-to-action; R integration for incorporating statistical and analytic algorithms and libraries written in the R programming language for more advanced analysis, data mining, and pattern recognition; historical database to allow systems to identify patterns from on sensor data, based on past behaviors enabling real-time analysis for preventive maintenance on machinery and equipment; and advanced in-memory management to accelerate processing speed with built-in support for Hadoop and Massively Parallel Processing databases like HANA and Kognitio.
“Creating IoT solutions is all about speed, agility and interoperability,” said Ben Hennelly, CEO, Decisyon. “Decisyon 360’s new capabilities further simplify development and the utilization of resources across IoT ecosystems. With the tight integration of CEP/BRM and advanced data analytics technologies into our platform, end-users and developers no longer need to use disparate tools and custom coding to build end-to-end solutions.”
Decisyon 360 is designed to unify data aggregation, advanced analytics, decision-making, and execution capabilities to make it easier for users to work in a collaborative environment. With the platform, companies can monetize big data by aggregating and analyzing information from a very broad set of data sources, predict patterns and events, and take strategic action.
This kind of collaborative and cross-purposed platform is important to any business hoping to use the edge of the IoT for Fog computing, because it can take inputs from so many different types of systems and aggregate them into one, simple system for review. Without that ability, data becomes meaningless.
Edited by
Dominick Sorrentino
