Digital-first companies, such as Amazon, Netflix, Google, and Facebook, have, in some ways, perfected the art of data and analytics — using data to drive business decisions. It is increasingly hard to compete against these providers without integrating analytics into critical business practices. The corresponding transformation in data-oriented analytics capabilities, enabled by modern data architectures (NoSQL, Hadoop, etc.) and cloud-based analytics processing tools, is now available to all companies through either vertically developed solutions or cloud platforms. Many analytics providers promise to bring this data oriented decision into every organization. They range from large consulting organizations, to cloud providers down to specialists in a specific business function for a specific industry vertical.

Similar to other vertical solutions, video service providers have a unique set of analytics requirements      that can help them optimize the design, delivery, monetization, and operations of premium video services. Many analytics solutions providers focus on a narrow subset of the analytics data from within a siloed architecture which creates the need for multiple self-contained tools providing piecemeal data insights. However, best-in-class analytics solution providers deliver a unified analytics framework, that can bridge inherent data silos to provide comprehensive data insights, as well as the deep insights required by individual business units and departments.

Today’s service providers are moving into a new generation of converged OTT services, defined by their ability to serve customers video content on multiple devices and multiple networks and different delivery standards. Many service providers are facing a migration of consumers from existing pay TV services, including legacy components delivered to set-top boxes, to converged OTT services offering. Others are developing more greenfield managed IPTV or OTT video services. Regardless of the nature of the service, monitoring analytics in real time to ensure service availability and performance is required to effectively compete with the digital-first video providers.

Both the technical and business challenges of these services mandate that service providers invest in analytics, and start the process of transforming their organizations to make better data-driven decisions. From a technology perspective, the shift to enable adaptive bitrate (ABR) with monitored quality of service (QoS), and the need to effectively manage QoS across multiple networks and device types increases the complexity of this challenge. From a business standpoint, the ability to understand consumption and monetization together with operational data helps with making better  content  licensing, promotion, and investment decisions.

There is no one-size-fits-all solution to analytics. Attempting to fully define the endpoint can leave organizations stuck in a data quagmire in which developing a long-term roadmap and attempting to define future needs, in an organization with little history of data-based decision making, results in very high expenses and long cycle times. Taking small, simple steps within a well-architected framework is often a better approach to starting the analytics journey.

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