Apparently there are many other data modelling methodologies besides relational modelling. In the data warehouse and BI world, the key word "multi-dimensional model" has been overwhelming for more than 2 decades. Kimball's theory on creating dimensional models has been well adopted into the industry. What we have found out, based on many people's (hard) experiences, is that the multi-dimensional data models are quite fit for data analysis purposes and it fits into the analytical mind of most business world. But, it is not a proper model for maintaining a large data warehouse where multiple data sources are ETL-ed into a single-version-of-truth.
The object-oriented modelling has been invented into the database world more than 10 years ago. As it is now, I can only see that Oracle has adopted some parts of this methodology into its commercial product. Maybe OO is just not the right way for managing the data, at least in the OLTP/OLAP world.
In the data warehouse modelling world, one of the key challenges to every data warehouse, is how to keep the history of data. Different data has different profiles. Some changes often, some needs to have a traceable history of the changes, some never changes, some only needs the most current change. To model the different enterprise data and keep the histories in a good manner, the concept of anchor modelling has just been discussed in the last ER conferences. It will be valuable to take a read into this topic and get to know more details about the method.
