In the past, those 2 problems could not be resolved without creating a new data model yourself or creating ad hoc reports via exports in f.e. excel. This meant recreating queries and measures from the original data model, which makes it error-prone and no longer secure and qualitative. Data will be duplicated into multiple data models, and risks occur about the correct usage of KPI definitions into the different reports.
Since the introduction of Composite models in December 2020, you have a valid alternative for the above-mentioned cases. Composite models give you the possibility to combine multiple data models into 1 new (linked) data model. Also, you can expand an existing data model with your tables and measures without changing the original (enterprise) data model. This allows key users to fully exploit the advantage of centralized data models, with the flexibility to add their own KPIs and mappings to increase self-service reporting.
Some advantages of this new approach:
There are however some limitations and important remarks to take into consideration: