Modern companies store and process huge arrays of heterogeneous information such as bills, transactions, Internet traffic, call records, social network posts, emails, equipment logs, sensor readings, and much more. Special-purpose Big Data systems can help businesses benefit from such data.

These solutions ensure highly accurate real-time analysis of bulk unstructured data, including text, video, and audio. The analytical engine of Big Data systems reveals unobvious patterns which can be used to forecast demand fluctuations and identify factors affecting the market, customer behavior, and purchase decisions.

Big data analytics provides an unparalleled opportunity to understand the quality and causes of customer experience. But how can operators unlock the value of analytics? Rising customer expectations and intense competition are forcing operators to deliver tailored customer experiences, across ominchannels, with outstanding quality, despite the network demands of advanced services.

Big Data analysis allows for;

• Faster collection of information, both from IT systems and external sources
• Improved report quality and solution efficiency by considering more parameters
• Creation of forecast models and simulation of event scenarios depending on various combinations of factors
• Reduced costs of information obtaining from various sources, filtering, and storing, mass media monitoring, and other similar tasks

• Customer expectation: Customers demand customization, quality, consistency and relevance in all their services
• Resource constraints: Customer expectations must be met without overspending on network capacity or operations
• Data silos: No single data source contains enough information to truly understand customer experience
• Scale and speed: Analytics solutions must provide real time insights that matter, even for the largest operator
• Challenging services: New services, such as VoLTE cannot be measured by traditional metrics
• Encrypted traffic: New approaches are needed to assure encrypted OTT services

• Customer experience insights: Automatically identifies customer experience symptoms, root causes and next best actions, resulting in reduced handling time, fewer escalations, and fewer rebounds
• Customer satisfaction insights: Applies patented algorithm to measure subjective customer satisfaction and predict net promoter score, for every customer
• Cross-domain: End-to-end correlation breaks down data silos and provides deeper insights
• Real time & offline: Supports custom analysis for marketing and planning while enabling real time insights for operations and customer care
• Encryption handling: Applies unique heuristics to identify and assure encrypted OTT services
• Multivendor: Handles events and metrics from any network node or system
• Scalability: Successfully processes billions of daily records in support of tens of millions of subscribers for the largest operators