Since more than 15 years I’m working with bitemporal data in Data Warehouse solutions. Meanwhile it is easy to design, build and populate tables for bitemporal data. But how to design and build bitemporal dimensional modeled Data Marts was new to me. Dirk Lerner does a very good job in explaining complex bitemporal stuff. His explanation helps you designing good SQL to populate bitemporal Star Schemas. Dirks presentation and explanation about bitemporal Data Marts is excellent!
Dirk Lerner and his presentation on bitemporal modeling at first gave me a brain freeze. However, his explanation of using a Data Vault satellite to track changes over time and collapsing the changes into a dimension for analytics was not only a requirement for financial reporting in Germany but also quite ingenious.
The first session at Data Modeling Zone Europe 2018 in Düsseldorf, was a session about bitemporal data by Dirk Lerner. The session was and is an extract from his current training Temporal Data in a Fast-Changing World, which is now available as open and private training [Link].
At work I just started at a new customer and was part of the data warehouse team, who was assigned the task of building the Data Vault Data Warehouse. We were developing the Data Vault generator. At that point we used an end-date for the business time. I remember the complexity for updating the old records and the time for the server it costs to do this. Especially when you want to add rows in between. To load history, for example, from old sources.
The training is led by Dirk in an interactive way.