Currently, I think there are two main approaches to Data Warehouse Automation
- Data Warehouse Generation: You provide sources, mappings, datatype mappings etc.. The tool generates code (or artifacts).
- Data Warehouse Automation (DWA): The tool not only generates code / artifacts, but also manages the existing Data Warehouse, by offering continuous insight in data flows, actual lineage, row numbers, etc..
The difference might seem small, but IMHO is visible most clearly whenever changes occur in the Data Warehouse – the second class of tools can handle those changes (while preserving history). With the first class of tools provide you with the new structures, but you need to handle the preservation of history yourself (as you would’ve without DWA).
Read on for a contrast of these two approaches.