Development of a predictive model based on time series that allows predicting the failure of mobile coverage equipment with 92% accuracy Predict the type of failure that a coverage base station will present, developing a predictive classification model with 78% accuracy.

Save the company time and equipment maintenance costs, predicting the type of power supply that guarantees constant operation with 84% accuracy. Construction of ETLs for the automation of reports.

Identify new insights and fraud trends on company sales

Improve the percentage of fraud detection in the company through a predictive model that identifies a fraudulent sale with 90% accuracy.