In human health and life sciences, researchers extensively collaborate with each other, sharing biomedical and genomic data and their experimental results. This necessitates dynamically integrating different databases or warehousing them into a single repository. Based on our past experience of building a data warehouse called GEDAW (Gene Expression Data Warehouse) that stores data on genes expressed in the liver during iron overload and liver pathologies, and also relevant information from public databanks (mostly in XML format), DNA chips home experiments and medical records, we present the lessons learned, the data quality issues in this context and the current solutions we propose for integrating and warehousing biomedical data. This paper provides a functional and modular architecture for data quality enhancement and awareness in the complex processes of integration and warehousing of biomedical data.