"We wished we had known Data Virtuality from the beginning when we started with our machine learning processes. This could have saved us a lot of time and energy. Data Virtuality is now a very essential part of our daily life as a data scientist. It helps us to capture, mix and consume data from different sources very easily. Thereby we can save time and focus more on the end result. Exciting times ahead."
"One of the most important learnings that we got out of this journey is how important data integration is for the machine learning process. And this refers to all parties involved: data architecture/analyst team as well as the data science team. Data Virtuality helped us to reduce the grunt work and eliminate idle time."












