Big data can be defined as a large volume of data, both structured and unstructured, that cannot be stored directly in a database with proper processing. Big data analytics is the IT offerings which utilizes several data mining for example text mining and predictive modeling. They help telecom service providers to extract real-time activities and support decision making in business. Telecom firms store large amount of data consisting of customer details, in their databases.

With the help of big data analytics, data can be first sorted, mined, processed and then stored systematically. This helps in improved customer services and bottom lines, along with intelligent network planning, customer experience, and decrease in customer churn. Resultantly, it provides assistance in upgrading the business models and optimizing the profit for telecom industry.

There are several reasons behind incorporating big data in telecom firms. Some of them are the urgent requirement to increase the revenue, need to bring in new business and prevent consumer churns, in order to defend the present revenue, and saturation of data in the market. To overcome these factors, there are various distribution channels available in the market that would help sorting and storing of data.

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Moreover, there has been a gigantic rise in usage of data, where the data deluge has come to a halt. The telecom sector is rising with a big chaos and unstructured data. Moreover, the revenue generation has also declined. Keeping these factors in mind, there seems to be a more-than ever urgency to integrate big data and analytics industry.