Benefits for Cable Operators

Insight and analytics enable smarter actions to be taken in real time.  VIA by Vitria transforms operational performance improving the subscriber experience, increasing service levels, and enabling service staff to become more productive.
VIA accelerates incident detection and resolution and enables process automation. VIA ingests and integrates streaming data, at millions of events per second from multiple source files including service logs files, network telemetry scores, incidents, sensor data, and many others.  It delivers real-time analytics enriched with subscriber reference data providing both contextual awareness and situational intelligence.

  • Monitor Quality of Experience and Quality of Service in real time
  • Detect complex customer-impacting incidents faster
  • Automate conversion of alarms to incidents
  • Predict failure minimizing disruptions and service degradation
  • Leverage machine learning and predictive analytics to identify incident impact and prioritize incident response activities.
  • Support the self-help diagnostic process and reduce the number of service calls
  • Notify subscribers of issues and actions being taken for resolution


Use Cases

Improve service operational performance through insight and analytics that enable faster response.

  • Monitor Service Operations in Real-Time

    Quality of Service and Quality of Experience monitoring with VIA improves operational performance. Streaming data from multiple sources and subscriber data processed, analyzed and reported in real time improves KPI performance monitoring and speeds identification of performance anomalies. Visual analytic tools accelerate insight. Interactive controls enable exploration to diagnose problems. With the Dash Board Builder, interactive displays are easily built with interactive controls that support analysis exploration.

  • Reduce the Incident Lifecycle

    Accelerate time from incident detection to quality restoration and issue resolution by improving incident detection and root cause analysis then taking remedial action automatically where feasible. Advanced methods of anomaly detection in granular entity populations and machine learning uncover difficult to detect issues (false negatives) faster and cut through the alert noise with the delivery of a single intelligent alert. Advanced analytics and machine learning accelerate root cause discovery. Machine learning applied to historical incident data determines possible remedial action and can enable automated response

  • Predictive Maintenance

    Accurately predict when maintenance should be performed to avoid failure or degraded performance. This results in lower operating cost, higher availability, and less downtime. Leverage situational intelligence through sensor data, machine learning algorithms, and predictive analytics to monitor performance in real time. Predictive alerts can be automatically delivered to areas requiring attention. Data-driven analytics displayed through the visual dashboards improve maintenance planning and staff efficiency.

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