Earlier bachelor projects focused on how an in-memory data layer can change the way “traditional” transactional enterprise applications work. By eliminating redundantly stored aggregates, views, and indices, the applications became 10-100 times faster while extending application functionality and improving flexibility. Furthermore, the in-memory data management enables analytics on the transactional data and eliminates costly transformations to external data warehouses. Consequently, a set of totally new applications becomes feasible with reduced total cost of ownership as a side effect. These applications enable businesses to get real-time insights, make more confident decisions, anticipate and react to changing conditions, and to become more flexible while being more effective by taking advantage of their data.