Detailed Platform Architecture

StreamAnalytix workflows can be executed on cloud or in-premise infrastructures.

StreamAnalytix integrates a comprehensive set of big data technologies to enable continuous analysis of data in motion and at rest across all stages of data processing, such as: data ingestion, data preparation, analytics, machine learning, data visualization, actions and alerts, and data sinks. And, offers an integrated development environment (IDE) that supports the entire application delivery lifecycle: design, build, test, deploy, and monitor.

Pre-integrated Drag and Drop Operators

Use a drag-and-drop visual interface which provides abstraction over a mix of complex big data technologies . Operators include an array of data sources, processors, advanced analytics and machine learning algorithms, and emitters.

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Leveraging continuous integration, delivery, and deployment(CI/CD) in StreamAnalytix

Continuous Integration and Delivery (CI/CD) is a set of automated SDLC practices and methods that enable frequent and error-free releases…

Operationalize Machine Learning at Scale with StreamAnalytix

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blog Sep 02, 2019

Detect and prevent insider threats with real-time data processing and machine learning

Insider threats are one of the most significant cybersecurity risks to banks today. These threats are becoming more frequent, more difficult to detect, and more complicated to prevent.

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