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Empirix has released a new analytics platform that turns terabytes of data into real-time intelligence for improving customer experience and performance management as well as strategic business decision making. Empirix IntelliSight is the first solution of its kind designed to remove much of the cost and implementation barriers associated with Big Data in mobile, telecom and enterprise-wide deployments.

Organizations can use Empirix IntelliSight to easily unlock insights from information-rich network feeds and efficiently enrich and correlate them with existing warehoused data for deeper insights. Empirix ’s unique application packages, algorithms and visualization options ensure that users anywhere in the company can quickly generate intelligence and fully explore the nuances behind those results.

“The vast amounts of data generated by communications networks are a valuable source to understand customer behavior and usage patterns. Empirix IntelliSight cuts through the noise and provides actionable intelligence by applying real time analytics, enabling CSPs to differentiate based on improved customer experience,” said Anil Rao, Analyst at Analysys Mason

Communication Service Providers (CSPs) face unprecedented challenges when it comes to Big Data. As networks have become more sophisticated and 4G services proliferate, the amount of apps and consequently data they generate is increasing daily. Customer bases and applications are expanding as mobile technology becomes more accessible. New requests, devices, and ideas are continuously being introduced and usage patterns seem to shift daily.

Large enterprises are contending with similar challenges as they attempt to integrate voice and video with the traditional client-server data applications. Also, the aggregation of information from multiple applications, networks, locations and departments is fundamental to a complete understanding of performance and business issues.

Companies urgently need intelligence to both stay ahead of performance issues and effectively navigate competitive landscapes. However, they have run into significant roadblocks when it comes to quickly and efficiently deriving meaning from so much disparate information. 

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