Hitachi Live Stream

Minimize downtime with real-time monitoring and fault detection

Smooth operations translate into a well-run business. But when a company’s network suffers from downtime, the bottom line suffers too. We understand the risk and cost of that downtime. Hitachi Live Stream uses the Internet of Things to provide real-time data monitoring and actionable alerts that greatly reduce the incidence, impact and duration of service outages.

Identify problems before they disrupt service

Every action has a reaction, making agile operations critical in an age of digital disruption. Hitachi Live Stream delivers real-time insights to predict, prevent and respond to impactful events.

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Success story: Reducing duration of business impacting events

Our client operates a national internet protocol (IP) network to support the delivery of communications services to its subscribers. Video service outages caused by faults in the infrastructure are difficult to detect and isolate and can increase the duration of customer-experienced interruptions.

  • Delayed identification of customer-impacting events by network operations team
  • Limited view of network equipment health and service performance across the network
  • Inability to quickly isolate network location and equipment information that supports triage
  • Lack of consolidated view of network performance data
  • Reactive approach to network events

 

Implement the Hitachi Live Stream platform enabling real-time insights to support prediction, prevention and accelerated response to events affecting business operations.

  • Integrate reference data from switchers and routers, network taps, brokers and probes to capture data from the IP network providing complete visibility to the smallest meaningful segment of the known footprint
  • Provide network operations users real-time network performance metrics and events details including anomaly isolation
  • Correlate internal and external datasources, such as IVR, social media and weather data to provide additional outage event detail
  • Apply data science models to identify predictive indicators utilizing machine learning, Gaussian statistics and thermodynamic entropy calculations
  • Reduced duration of business-impacting events by more than 50% by monitoring service delivery infrastructure in real time
  • Reduced asset downtime by proactively monitoring key assets and setting alerting notifications
  • Provided live views of the health or status of key assets
  • Reduced cost to investigate potential business operations issues by 25%
  • Implemented dynamic alert logic to detect anomalies and more subtle issues