A technique for generating synthetic data as input for a machine learning process that recommends radio access network, RAN, configurations is presented. An apparatus implementation is configured to generate synthetic data from a noise input, using a trained generative machine learning model, wherein the generative machine learning model has been trained together with a discriminative machine learning model as adversaries based on non-synthetic data. The non-synthetic data comprises non-synthetic configuration management, CM, parameter values, non-synthetic RAN characteristic parameter values and non-synthetic performance indicator values. The synthetic data is in the same form as the non-synthetic data and comprises synthetic configuration management, CM, parameter values, synthetic RAN characteristic parameter values and synthetic performance indicator values. The apparatus is also configured to output the synthetic data for the machine learning process.