Uso de ferramentas de business intelligence para identificação de contratos com fornecedores inidôneos ou suspensos

Abstract

Year after year, data has become more prominent and useful, growing exponentially and proving to be invaluable across various sectors. To extract value from these often unstructured and chaotic data sets, understanding and studying data science became essential. This led to the development of highly valuable techniques, concepts, and tools for extracting insights from these data sets. In this context, Big Data emerged, enabling the processing of large volumes of data. Business Intelligence allows us to understand business rules and identify patterns within these vast information sets. Recognizing the accumulation of large data sets in public procurement, public agencies saw the need for proper data management to prevent financial losses. Over the past five years, public tenders have surpassed 50 trillion reais in contracts. Despite efforts to minimize fraudulent or risky contracts, the resulting amounts are still substantial due to the scale of these contracts. Therefore, this work aims to demonstrate the process of implementing techniques and tools to map public procurement contracts with potential risks.