This project arose from the need of the users of the Customer Billing area of América Móvil Perú SAC to obtain continuous and timely information on commercial indicators associated with their various activities. Specifically, the study focused on the calculation of penalty charges related to the reinstatement of equipment, a process that varied depending on the reason for line deactivation and was constantly adjusted due to market competitiveness and regulatory changes. The objective of the project was to conduct an in-depth analysis of the different schemes used by analysts to generate their indicator reports. This analysis identified the critical data required for each scheme and ensured that all reports followed a standardized framework, establishing consistent rules for data homogenization. To achieve this, a Business Intelligence (BI) solution was developed using a data mart, allowing the automation of calculations, the integration of dispersed data sources, and the reduction of reporting times. As a result, decision-making processes were improved, and the efficiency of commercial operations was significantly enhanced.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Business Intelligence with Data Mart to Reduce Reporting and Indicator Generation Time

  • Hugo Vega-Huerta,
  • Eiko Nalvarte-Almeida,
  • Ivan Adrianzén-Olano,
  • Oscar Benito-Pacheco,
  • Javier Cabrera-Diaz,
  • Rubén Gil-Calvo,
  • Juan Carlos Lázaro-Guillermo

摘要

This project arose from the need of the users of the Customer Billing area of América Móvil Perú SAC to obtain continuous and timely information on commercial indicators associated with their various activities. Specifically, the study focused on the calculation of penalty charges related to the reinstatement of equipment, a process that varied depending on the reason for line deactivation and was constantly adjusted due to market competitiveness and regulatory changes. The objective of the project was to conduct an in-depth analysis of the different schemes used by analysts to generate their indicator reports. This analysis identified the critical data required for each scheme and ensured that all reports followed a standardized framework, establishing consistent rules for data homogenization. To achieve this, a Business Intelligence (BI) solution was developed using a data mart, allowing the automation of calculations, the integration of dispersed data sources, and the reduction of reporting times. As a result, decision-making processes were improved, and the efficiency of commercial operations was significantly enhanced.