Bioprocess data creates value for biotech companies. No doubt. Accelerated process development. Investigation & troubleshooting. Operations excellence. Assess optimization potential. Just to name a few use cases. Industry 4.0. Digitalization of the processing environment. New sensor technologies and data integrity requirements disrupt how process data is managed and analyzed. As a result, requirements for data management and bioprocess data analytics change dramatically. Today, data sources are very complex and multidimensional. Spectra from spectroscopic sensors, such as NIR and Raman, images from flow cytometry and in-line microscopes, mass spectrometry chromatograms, time-series sensor data, quality data, software sensors. Upstream. Downstream. Just to name a few. New solutions capable of managing and analyzing all process-relevant data types are necessary.