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This report describes the implementation of the data pre-processing for a novel anomaly detection technique. Proposed anomaly detection technique is based on using stochastic matrices as input for convolutional neural networks. Pre-processing step transforms raw data into 3d tensors combining stochastic matrices for a given event. Proposed solution for pre-processing is split into data reading part, which is parallelized with Dask and data processing part, which is parallelized with Spark. Datadoi:10.5281/zenodo.4591034 fatcat:mtwfl6p5jzbc7drjdgha6amubi