The What: Qligent has updated its Vision Analytics solution with an improved open-platform that harnesses the power of data mining, machine learning, and predictive data analytics. Vision Analytics exists to address three main concerns: user engagement, silent sufferers, and audience churn. Qligent will exclusively showcase Vision Analytics at a special stand (14.C19) from September 13-17 in the RAI Exhibition and Conference Center; Qligent will also retain its usual location at Stand 8.E47.
The What Else: Qligent has added several important new features to Vision Analytics for IBC2019. Key Quality Indicators (KQIs) to show specific performance parameters for broadband and internet delivery; service-independent correlation engines to identify and reconcile problems over any delivery network; an intuitive Reports Builder application that allows users to create actionable reports, customizable to each service; a new Dashboard Constructor for web and mobile devices that allows users more flexibility in adding widgets, graphs, and other customized reporting elements meaningful to their operations; and a refined predictive analytics model to more effectively combat buffering issues for IPTV, OTT, and mobile delivery services.
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“Vision Analytics not only monitors network performance in real-time, but leverages machine learning and other data science technologies to predict conditions that, left unchecked, could sour viewers on the media brand,” said Ted Korte, CTO, Qligent. “Users will know which events cause viewers to become disengaged, and how to keep track of subscribers by merging Quality of Experience with Qligent’s true end-to-end technology. This gives service providers a powerful prevention-oriented toolset, as well as cloud-based quality assurance across every distribution network out to each viewer’s home and mobile device.”
Qligent’s unique deployment of networked and virtual probes creates an end-to-end, controlled data mining environment to produce trusted and secondary opinion datasets within Vision Analytics. The analytics engines are immune to variables, such as operator error, viewer disinterest, or user hardware malfunction, assuring that the integrity and variety of the data is maintained. All findings are presented on a user-friendly dashboard and reports that summarizes key performance indicators (KPIs), key quality indicators (KQIs), and other vital criteria pertaining to multiplatform content distribution across creation, delivery, and consumption.
The Bottom Line: Vision Analytics addresses the “4 Vs” of big data: velocity, volume, variety, and veracity. Its engines leverage scalable cloud processing to manage a nearly limitless number of static, dynamic, or event-based datasets to help broadcasters, MVPDs, and OTT service providers quickly address issues and take corrective and preventative action. The software samples video content and aggregates data from a variety of systems and components throughout the ecosystem to understand and correlate the factors that contribute to higher engagement. With a reliable data set, users can develop a host of analysis results, visualizations, and automated reports to suit unique business needs.
