Most data models are static, in that they represent the properties of, and relationships between, business entities at a point in time. However, for a system to properly function over time, its data model must be designed to support data update in response to changes in the real world. Dynamic Data Modeling covers not only static data structures but update policies, by considering issues such as:
what real-world changes must be captured in the database?
what are the requirements for preserving a record of the historic state of the attributes and relationships of any entity?
why must changes in attributes and changes in relationships be dealt with differently?
do we also need to record changes in our state of knowledge of the real world?
what aspects of the time dimension need to be taken into account?
This presentation provides an overview of the Dynamic Data Modeling toolkit, with which experienced data modellers can effectively support projects delivering BI or operational data resources with a significant time-variant component.