Examples of using Event processing in English and their translations into Japanese
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LoopEdge lets you collect data from industrial systems like PLC, DCS, Sensors or Historians and run Event processing, Lambda functions or Edge Applications from the marketplace locally- all with a offline first deployment.
Other advantages include the lack of bugs in the fundamental part of an application, easy maintenance, easy handling with ten keys and enter key, templates for developing applications, and automation of event processing.
LoopEdge lets you collect data from industrial systems like PLC, DCS, sensors or historians and run applications locally on top of the data, such as event processing, Lambda functions, machine learning models, and more- all in an offline first deployment.
New Rules Features- Stateful Rules services, decision tables and Rule agent support will further enable business event processing with an event-driven architecture(EDA), as well as allow non-developers to construct business rules and enable rapid deployment.
Complex Event Processing.
Notification service by event processing.
Complex Event Processing and EDA?
TK_SUPPORT_SSYEVENT Support for event processing of subsystems.
Data collection/event processing base SmartEDA products are required separately.
So we should add an event processing method for WindowClosing event. .
Deploy event processing, machine learning models and Lambda functions at the edge.
Azure Stream Analytics is Microsoft's serverless real-time analytics offering for complex event processing.
This enables to easily express and run Complex Event Processing(CEP) on your streams of data.
Event processing and viewing, reports, users and permissions will be different for each Pandora FMS installation.
TIW provides lifecycle event processing services for roughly 98% of all credit derivative transactions worldwide, worth $11 trillion.
They can be used to provide complex event processing systems that can provide automatic or actionable outcomes for your enterprise.
Azure Stream Analytics- Stream Analytics is an event processing engine that helps uncover real-time insights from devices, sensors, infrastructure, applications and data.
Event management tools provide administration and monitoring of the event processing infrastructure, monitoring of event flows, and visibility into event generation and processing statistics.
Stream Analytics is a fully managed real-time analytics(complex event processing) service that enables you to detect anomalies and archive data from your IoT devices.