EXAMINE THE VARIOUS DATA MINING TECHNIQUES OF TELECOMMUNICATION COMPANIES IN NIGERIA

The study examines the various data mining techniques employed by telecommunication companies in Nigeria to enhance decision-making, customer relationship management, fraud detection, and service optimization. With the rapid growth of the Nigerian telecom industry and the increasing volume of subscriber data, the application of data mining has become crucial for maintaining competitive advantage and operational efficiency. The research adopts a descriptive survey design, drawing data from major telecommunication operators such as MTN, Glo, Airtel, and 9mobile. Both primary and secondary data were utilized, and analysis was conducted using statistical and comparative methods. The findings reveal that key data mining techniques such as classification, clustering, association rule mining, and regression analysis are extensively applied to predict customer churn, detect fraudulent activities, and personalize marketing strategies. However, challenges such as data privacy concerns, inadequate technical expertise, and infrastructural limitations hinder full-scale implementation. The study concludes that effective adoption of data mining tools significantly improves business intelligence and customer satisfaction in Nigeria’s telecom sector. It recommends continuous investment in data infrastructure, staff training, and stronger data governance frameworks to maximize the benefits of data mining technologies.