Over time, information changes in complex ways. For example, the classification of products into product groups or the pricing ranges of products by target group, sales channel, discount system and much more change over time.
Is temporal data just there to be stored? Because one can simply do it? Or wouldn't a valid business need be important in deciding whether I should bother? And should I use a particular technology to do it? Or design my own processes for temporal data?
In this session Dirk Lerner will give an insight into bitemporal data use cases and why they are important and fundamental to today's business requirements. Afterwards he visualizes the procedure of bitemporal historization of data using a simple example. Finally, Dirk presents the available technologies that have already implemented (bitemporal) historization of data.