Rainfall data are widely used to predict regional rainfall. Limited rainfall data is a problem that has an impact on decreasing accuracy, one of which is in the area of South Sumatra. This can be overcome by using satellites. However, to utilize satellitebased rainfall data, it is necessary to carry out an analysis to determine the accuracy of rainfall data. This research aims to evaluate rainfall data from the GPM satellite and PERSIANN satellite with validation and calibration analysis so that the value of rainfall data from the Satellite is close to the measurement result and can be used to estimate monthly rainfall. In this study, the data used were measured monthly rainfall in the field, GPM, and PERSIANN obtained from 9 South Sumatra districts for 2019 until 2021. The research method was validated using correlation coefficient, Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). Calibration is done using a combination method, a solver algorithm in Microsoft Excel, and manually. The estimated monthly rainfall analysis is carried out using the isohyet method with the IDW interpolation method. The research results were obtained based on the validation and calibration of monthly rainfall data showing that data from the GPM showing it is closer to the results of field rainfall measurements than the data obtained from PERSIANN satellite. Based on the results of research on satellite data that has been calibrated, it can be used to estimate monthly rainfall in the South Sumatra Region