Adopting Big Data Analytics Strategy in Telecommunication Industry

Abstract

Nowadays, adopting big data is a reality. Telecommunication company or telco must find the right solution to store all information available across the organization to maximize revenue using the analytics. The solution must be able to harness the large volume, variety, and velocity of the data available. One of the challenging actions is how to perform decision making and analysis in real-time. Some of the operational decisions may not comply with the corporation policy which makes it hard to keep up with the modern evolving business environment. Telco needs a platform to improve the business process and sustainable and profitable growth. The significant impacts should involve improvements of the customer experience and more reliable network quality, thereby reducing the customer churn rate. Big data and machine learning represent today's trends for the analytics. With big data analytics, the service provider can utilize the full potential of their data set by correlating, processing, and deciphering the hidden information from it. The conventional machine learning tools without big data are becoming inadequate as the trends shift towards distributed and real-time processing. The service provider needs the solution big data-driven which supports them to achieve timely manner and more accurate insights via the predictive analytics, text mining, and optimization. This paper also explains the characteristics of big data, and several uses of case implementing machine learning inside the big data platform related to telco operation such as mobile fraud detection. A well-known big data processing framework such as Hadoop indicated that there is an integration with machine learning tools such as Mahout, H2O.ai, R-Hadoop components, and KNIME. The advantages of these tools are evaluated based on their scalability, ease of use and extensibility features.

Application of Big Data Analytics in Telecommunication Sector Company in Sri Lanka: with Reference to Marketing Perspective

“…This implementation will express the speed of processing any BDA method, including customer segments, to improve providing real-time insights. Imran and Yayah (2017) suggest that BDA can use in telecommunication companies for Network Infrastructure Service, Churn Prevention, Customer Relationship and Experience, Product Development and Fraud Detection. Offering new products to the customers is an essential requirement to be retained as the market leader in the telecommunication sector (Phavy, 2013).…”

“…Therefore, telecommunication companies have established new projects to collect data on user behaviour in tablets and mobile phones in order to create buying patterns using BDA. These projects have been significantly improved in the revenue of the companies (Imran, et al, 2017). Hence, it can recommend to the Telco company to implement BDA in other applications such as network monitoring, forecasting and identifying consumer patterns relating to telecommunication.…”

Big Data Integration Solutions in Organizations: A Domain-Specific Analysis

“…This research can be extended by improving multiple levels of protection technologies in the big data platform. Yayah et al explained a few use cases of machine learning implementation in big data platforms [39]. Scalability and extensibility are the parameters used for the evaluation of BDI technologies.…”

Maturity and Value of Big Data in the Telecommunications Sector in the Republic of Yemen from the Prospective of Information Technology Professionals

“…Nevertheless, Yemen does not take use of the potential advantages of big data across the Telecommunication sectors since it lags behind the rest of the world in big data technology. Telecommunication companies will be able to adopt big data technologies and solutions that will provide competitive value and the possibility to encourage a new Telecommunication industry in Yemen and require new occupations [14].…”