For prioritizing requirements with data feeds having complex relationships, both a matrix and a data model can be used, but a matrix is generally more suitable for initial prioritization and a data model is better for representing the structure and relationships of the data itself.
Here's why:
Matrix:
A matrix can help prioritize requirements based on factors like business value, technical feasibility, or effort required. It provides a structured way to assess and rank different requirements.
Data Model:
A data model, like a class diagram or entity-relationship diagram, is used to represent the structure and relationships of data within a system. It helps understand how different data elements interact, which can be crucial for identifying and addressing complex dependencies.