  This paper presents a systematic review of common analytical data
architectures based on DAMA-DMBOK and ArchiMate. The paper is work in progress
and provides a first view on Gartner's Logical Data Warehouse paradigm, Data
Fabric and Dehghani's Data Mesh proposal as well as their interdependencies. It
furthermore sketches the way forward how this work can be extended by covering
more architecture paradigms (incl. classic Data Warehouse, Data Vault, Data
Lake, Lambda and Kappa architectures) and introducing a template with among
others "context", "problem" and "solution" descriptions, leading ultimately to
a pattern system providing guidance for choosing the right architecture
paradigm for the right situation.
