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Prominent Use Cases Of Data Science In Telecom Industry

With the growing prominence of Big Data, Data Science has become a necessary major commodity that helps enterprises across different sectors to reap the benefits of Big Data to its full potential. Data Scientists are very much capable of exploring new ways of new ways to implement big data solutions that can help enterprises to scale & grow. Big Data has become the new oil for the business development process. Data Science has become the major source that helps in delivering the benefits of Big Data.

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Now, let’s look at the different use cases of Data Science in the Telecom industry.

  • Fraud Detection With Data Science

As the Telecommunication industry would generally be having over several millions of customer base, there are more chances of occurrence of fraudulent activities. Illegal access, authorization, fake profiles, cloning, etc. are the different types of frauds that are common in the telecom industry.

By deploying the Data Science Fraud Detection model, telecom enterprises can accurately detect & prevent frauds at the right time. This model makes use of unsupervised machine learning algorithms to analyze & identify specific behavioral patterns or characteristics that are abnormal, hinting towards fraud. This technique is very efficient as it generates a real-time response to fraudulent activities.

  • Predicting Changes In Customer Interests With Data Science

Most telecommunication industries rely on Predictive Analytics in Data Science to accurately predict the changes in their customer behavior. Based on the predictions generated by the predictive analysis model, enterprises can make faster, better, and make data-driven decisions.

This Predictive analytics model makes use of users’ historical data to build accurate forecasts. If the analyzed data is highly accurate, then the generated predictions would also be highly accurate.

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