Mining operations depend on accurate and timely information from their truck fleets to optimize maintenance and decision making. However, sensor alert data captured by platforms like VisionLink and offered by manufacturers like Caterpillar have significant limitations, such as manual access, data windows limited to 14 days, and risks of error due to human manipulation. This scenario highlights the need for automated solutions that integrate and log operational data for efficient exploitation. This study proposes a solution based on ETL (Extract, Transform and Load) processes implemented in Cloud Computing. The developed methodology allows the automated integration of data from VisionLink APIs into a centralized Cloud repository. Subsequently, the information is displayed and analyzed in Dashboard using a BI tool, facilitating decision making. The results demonstrate a significant improvement in data accessibility, reliability and analysis, reducing manual tasks and associated risks (85%). In addition, data historicization is guaranteed beyond the limit imposed by the provider. These findings underline the positive impact of cloud and API technologies on business intelligence, offering a scalable and adaptable solution for the mining industry.