Abstract
Medical and translational research generate clinical data through patient data management system and these data along with the clinical research data need to be integrated and stored in a data warehouse (DW). Clinical DWs are repositories for combining various data sources using specific analytical tools that accelerate data processing and analysis. Using clinical data integration techniques, it is possible to combine data from many electronic health record systems into a single, comprehensive source, giving practitioners access to all the data they require for precise, standardized care. Integrative approaches have the potential to enhance disease phenotypic prognostics and predictability, which will ultimately contribute to better treatment and prevention. It will cover the data security, protection, and privacy which are an integral part of data warehouse concept. All of these strategies are extremely useful that, if used properly, might raise the standard of medical care, lower healthcare expenses, and also reduce disease burden.
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