In order to recognize and anticipate customer's requests, reinforce and manage the communication and operational flows, analyses of which are the services that the consumers demand to the energy companies are extremely important. To improve each relationship channel and to recognize the customers' profile, expectations and needs, it has been necessary to reinforce the operational efficiency concerning costs and agility. Operational effectiveness answering the demands is pursued, considering the amount of services offered and generated by relationship channels, communication facilities and operational conditions provided by the companies. A huge amount of data had to be organized to represent this scenario and forecast the relationship. To represent it, models were created to monitor and predict customers' requirements based on historical and online data. There were established regional resources availability, weather conditions, problems concerning the energy distribution grid, as well as the motivation of the customers to use alternative medias or relationship channels. The big data treatment techniques were used in order to provide the necessary agility to achieve the monthly/hourly volume of data (millions of registers per month) and permit communication clusters' views.
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