Application of big data techniques to a problem

                               Application of big data techniques to a problem


Just think, Big Data is not the load of data. The data are there mainly in order to respond to real world problems. A classical example is the application of Big Data for a telecommunication company in order to foresee customer churn. After analyzing customer interactions, the history of their bills, and usage patterns, the organizations can make a customer segmentation to identify who is most likely to leave.

Once a churn risk model has been developed with help of machine learning methods, the enterprises that have the model at their disposal can get in touch with problematic clients by giving them personalized proposals, extra value for the services, or any special help required to them. This can highly contribute to the retention of customers while it leads to the reduction of the cost to attract new ones. The model continues to improve as it becomes more accurate with new information and time is passing by.

Even the same Big Data applications can be effective in some other domains. For example, in logistics, the companies can estimate the delays of delivery using the information about weather and traffic. And in medical care Big Data, with the help of wearable sensors, is capable of monitoring patients' health in real time. The possible business niches are uncountable – any place where the future can be predicted, processes can be automatized, or personal recommendations can be provided, Big Data will be the main driving force.

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