Fiscal control and monitoring of public management are issues of great importance and relevance, as they focus on preventing and mitigating corruption, thus benefiting governments in their management and performance, and thus citizens. Given the large amount of data involved in the management and functioning of a government, it is pertinent to apply data analysis methods to contribute to fiscal control. This paper aims to investigate data management for this purpose, starting with a bibliometric study to demonstrate the relevance and pertinence of the current study. It examines existing data collection techniques that may facilitate such control, data storage considering its nature and the possibilities that contribute to this end, and data processing through techniques that allow obtaining adequate information for further analysis and decision making. The necessary architecture and interoperability between systems is also discussed, as the existence of large amounts and types of data in governments makes it crucial to promote these practices for accurate and truthful analysis. Finally, data visualization is addressed since this topic is highly relevant as it allows for the identification of anomalies, where proper visualization promotes appropriate analysis and thus informed decision making. This work is useful for modern audit and fiscal control entities, since data capture, storage, processing, interoperability, and visualization are crucial elements that collectively enhance the ability to supervise public expenditure effectively, ensuring that public funds are managed with the highest standards of transparency, accountability, and efficiency.