Now with TAG’s MCS that voluminous raw data can be aggregated and correlated using the power of the cloud and machine learning, leveraging TAG data and metrics to create actionable insights. Using an open-source paradigm, the MCS serves as an aggregation engine capable of exposing the data collected by the MCM to standard third party analytic and visualization applications such as Elasticsearch, Kibana, Grafana and Prometheus to analyze and visualize data. For the first time, media companies will be able to measure internet networks and CDN performance across all of their signals and know where to shift workloads for optimum performance. It will identify cyclical errors within the log file noise and drive faster root cause analysis and recovery from intermittent issues. By aggregating data across multiple customers’ CDNs and internet networks, TAG will provide realtime CDN and network metrics to its customers, helping them steer around outages and congestion. It will correlate and identify problems across specific consumer devices, versions and platforms and identify content and delivery issues including bad source, origin, encoding; or CDN, regional or device problems, helping customers deliver interoperable signals. With TAG’s MCS, customers will be able to deliver an exceptional viewer experience that can be validated and measured.

“Until now,” Joyce added, “A lot of meaningful, insightful and actionable data was left in dusty logfiles that never saw the light of day. The Realtime Media Platform, with the MCS, provides users with the deep insight into quality, metrics and issues that will enable them to turn that data into a positive consumer experience with better curation, programming and improved integrity resulting in improved promotion, increased consumption and more customers with heightened loyalty.”

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