Mobile networks produce a huge amount of spatiMemporal data. The data consists of parameters of base stations and quality information of calls. The Self-organizing Map (SOM) is an efficient mol for visualization and clustering of multidimensional data. It transforms the input vectors on two-dimensional grid of prototype veeors and orden them. The ordered prototype yectDrs are easier to visualize and explore than the original data. Then are two possible ways to start the analysis. We can build either a model Of the network using state vectors with parameters from all mobile cells or a general one cell model trained using one cell state vectors from all cells. In both methods huther analysis is needed. In the Bnt method the distributions of parameters of one cell can be compared with the others and in the second it can be compared how well the general model represents each cell.