Automação de planilhas excel com Python: proposta para apoiar as tomadas de decisões comerciais na Beta Distribuidora

Abstract

This study presents the development of a data automation process to consolidate commercial performance indicators at Beta Distribuidora Ltda., replacing manual spreadsheet-based procedures with an automated workflow built using Python, the Pandas library, and integration with Power BI. This applied, qualitative, and descriptive research investigated how data automation can reduce rework, minimize operational errors, and increase agility in the availability of managerial information. The study began with a diagnosis of the previous manual process, which relied heavily on spreadsheet manipulation, repeated extraction of ERP reports, and extensive data treatment, resulting in significant processing time and a high risk of inconsistencies. Based on this analysis, an automation prototype was developed to standardize information extracted from reports C15 and C94, consolidate them automatically, and load the structured dataset into Power BI dashboards, eliminating repetitive tasks previously performed by the commercial team. The results demonstrated a substantial reduction in processing time, greater accuracy in the generated information, and improvements in data traceability and standardization. Automation reduced the monthly consolidation effort from approximately 22 hours to just a few minutes, strengthening evidence-based decision- making and improving the organization’s operational efficiency. The study concludes that accessible tools such as Python and Power BI can generate significant impacts on medium-sized companies, supporting digital transformation and enhancing internal information flows.