Qligent to show cloud-based video analytics

March 12, 2019
Qligent now offers a cloud-based solution to monitor the quality of video viewer engagement and protect media brand value across multiple ...

Qligent now offers a cloud-based solution to monitor the quality of video viewer engagement and protect media brand value across multiple delivery platforms. The company's Vision Analytics combines data mining, machine learning, and predictive data analytics to help its customers address video quality issues and take corrective action. Vision Analytics will make its North American debut at the 2019 NAB Show in April in Las Vegas.

Vision Analytics is designed to sample video content globally across any content distribution channel and monitor the viewer's quality of experience (QoE) on any platform, network, channel, or app at any given moment out to the last mile.

"While content can be king, viewers will quickly grow frustrated and move on to alternative content if they experience problems finding, accessing, or watching a particular show," said Ted Korte, CTO, Qligent. "Viewers are truly in control today, and if their viewing experience falls short of expectations, there are many other networks, platforms, programs, and services to choose from. Subscriber churn or audience erosion is costly and difficult to rectify."

Vision Analytics is designed to not only monitor network performance in real-time, but also leverage machine learning and other predictive data science technologies to provide information about conditions that, left unchecked, could sour viewers on the video provider's media brand.

"A broadcaster or MVPD can take corrective action to prevent quality of experience issues when armed with a rich data toolset that delivers insight into real-time performance and trends," said Korte, "Vision Analytics puts the power back in the hands of our customers. These problems can be prevented from happening in the first place when it's made clear that trouble is brewing."

Vision Analytics is designed to handle the "4 Vs" of big data: velocity, volume, variety and veracity. Its engines leverage scalable cloud processing to manage static, dynamic or event-based datasets. All findings are presented on a dashboard and reports that summarize key performance indicators (KPIs), key quality indicators (KQIs), and other criteria pertaining to multiplatform content distribution across creation, delivery, and consumption.

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