Adoção de uma ferramenta de Business Intelligence para tomada de decisão no processo de identificação de anomalias e manutenção no setor elétrico

Abstract

In this work, the importance of data management for companies and how data analysis can contribute to improving business are addressed. The need for tools and methodologies to handle the growing volume of generated data is emphasized. Relevant concepts and best practices of Business Intelligence are presented, discussing tools, data architecture, and modeling. In the electrical sector, data management and the importance of indicators for maintenance and anomaly detection are emphasized. The relevance of data management in ensuring the availability of quality and reliable electricity service is highlighted. The data modeling and architecture methodology in the Extraction, Transformation, and Loading layer is detailed, including the construction of Data Marts based on QVDs and business requirements for visualization and decision- making. The scalability and robustness of the developed tool, allowing its use in energy sector companies, are emphasized. The tool enables the creation of alerts related to critical data and monitoring data updates. It is concluded that the tool enhances processes by replacing manual approaches, offering an expanded view of the company’s data and providing a foundation for decision-making. The application is powerful and user-friendly for business users with basic data knowledge. In addition to scalability, its robustness is evident when using the Qlik platform, providing options for improving information utilization.