For years there has been a clear divide, both technological and conceptual, between the operational and informational aspects of data management. This has long been imposed by the limitations of the technologies supporting each of these spaces and the data stack they enforced on data processing. This reality even shaped organizations by splitting data owners and subject matter experts from analysts. Business intelligence (BI) professionals had to live with the fact that pulling real-time data from transactional systems for analysis could not be done without significantly affecting operational performance. Similarly, transactional application designers had to accept that data analysis could not be carried out in time to feed relevant insights into operational processes.