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WHITE P APER Improving Business Outcomes w ith Big Data and Anal ytics in Communications, Media, and Entertainment Sponsored by: HP Debra Osswald Greg Girard September 2012 IDC OPINIONwww.idc.com Information is emerging as the new currency of business and the basis for sustainable competitive differentiation, innovation, value creation, growth, and risk mitigation. If communications service providers (CSPs), cable operators, and communications/media/entertainment companies (CME companies for short) are toF.508.935.4015 survive the pressures exerted upon them by their dynamic and challenging new market environment, they must deliver consistently high quality of service (QoS) and personalized customer experiences while efficiently operating their networks at the highest available capacity. They must also innovate more frequently and cost effectively, uncover new business models, and create new differentiated servicesP.508.872.8200 valued by their customers. All of this requires that they manage the full life cycles of the vast amounts of customer, network, and usage data streaming from their operations and analyze this data for actionable insight — in real time, near real time, or offline, depending on the business context and objectives. Emerging Big Data management and analytical technologies, business processes, and decisionGlobal Headquarters: 5 Speen Street Framingham, MA 01701 USA management frameworks can help these organizations achieve their goals. SITUATION OVERVIEW Todays CME market and technology environments are characterized by: An increasingly harsh competitive climate A profusion of varied, high-volume, and high-velocity data streams Enterprise barriers to managing and analyzing new Big Data assets From the perspective of this white paper, the systems supporting CME companies CSP and content delivery network (CDN) operations (operational support systems, or OSS) and the systems supporting their customer, content, and partner assets (business support systems, or BSS) come to the fore as the key information technology (IT) barriers to managing Big Data assets for extracting actionable insight from them. However, additional barriers thwart these efforts as well — in particular, siloed organizational structures and incentives, disconnected cross-functional and multibusiness unit processes, and maladapted decision management frameworks.