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Streaming Data

Decisions in sync with speed of data

If your tools only run analytics on retrospective data, that could be a challenge that must be overcome by technology. You need solutions that can read, store and process complex, diverse real-time data in an automated manner. Cloudflux’s Streaming Data module can manage real-time processing and analysis of events from disparate sources to handle patterns and complex event relationships to generate real-time notifications for timely action.

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Cloudflux Real-time Processing of Streaming Big Data

Cognix Solution

Cognix platform offers a visual modelling environment that accelerates the design and deployment of streaming data applications.

Cloudflux solutions can monitor live streams of data and identify patterns, trends and correlations for smart decision making and process management.

Both historic and live streams of data can be analyzed in real-time.

Empower your applications with Machine Learning capability on streaming data.

Cognix difference

Flexibility to use different models like data flow, event flow, and Machine learning to build a Streaming Data model even using external sources using API’s.

Streaming Data model for real-time data analytics to predict key performance indicators (KPI) and even improve it.

Streaming data models that can be adapted for IoT.

An intelligent model can be built for massive data resources and can enable actionable insights by analyzing data.

Cloudflux Real-time Processing of Streaming Big Data
Cloudflux Real-time Processing of Streaming Big Data

Cognix Impact

Visual application development and one-click deployment environment.

Seamlessly integrate with external data sources and applications with the help of API’s.

Efficiently process, filter and manage data from various sources.

Real-time analysis of massive data resources to remediate at the right time.

When a significant pattern occurs, users are notified based on pre-defined business rules.

Streaming Data model can be re-used for IoT and real-time data streaming.

AI powered Streaming Data model is used for descriptive, predictive and prescriptive analysis of live streams of data.