The feature extraction capabilities of Machine Learning (ML) models have led to their wide adoption in a large variety of sectors: from anomaly detection for machinery, to user clustering and behavioral prediction, market trends predictions, or the analysis of text, sound, and image data. The performance of ML models heavily relies on their ability to perform pattern recognition on large amounts of data, which impelled companies to monitor their processes and build large data bases that could be used to train ML models, or even monetized through data marketplaces.