Real-time stream processing is essential for early warning and prevention of events that could have a significant impact on your business and systems. Use SQLstream to identify and trigger actions for threats like:
Anomaly Detection
Use automatic pattern and anomaly detection to identify operational risks and opportunities in real time
Use SQLstream to identify events which do not conform to an expected pattern to alert users or trigger actions and respond to un expected events.
Recommendations
Provide personalized recommendations to customers and users based on real-time events learned from historical context.
Analyze real-time patterns along with historical data to provide, understand and make recommendations to your users and customers.
Predictive Analytics
Machine learning is driving businesses to create predictive models that learn from patterns in historical data to identify risks and opportunities.
Build predictive models to monitor and prepare your operations, infrastructure and customer data for unforeseen events and new opportunities.
Monitoring
Use automatic pattern and anomaly detection to monitor data streams for performance or quality of service issues.
Streaming SQL analytics helps users determine if performance or SLAs go out-of-tolerance so that you can react to potential problems as they happen and reduce risks and costs associated with repair.
Guavus SQLstream’s mission is to make real-time stream analytics easy to use and own with a one-stop-shop solution that performs the best, has the widest footprint, never turns off, and can be developed and customized by data scientists and engineers alike.
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