Implementing Master Data Management on Healthcare Data Tools Like (Data Flux, MDM Informatica and Python)

Abstract

This article outlines a comprehensive approach to implementing Master Data Management in healthcare, focusing on the key stages of Extraction, Validation, Standardization, Matching, and Survivorship rules. The integration of powerful tools such as DataFlux, MDM Informatica, and Python enhances the efficiency and effectiveness of the MDM process.

The first phase involves data extraction, where relevant healthcare data is gathered from disparate sources. This data is then subjected to thorough validation to identify and rectify any inconsistencies or errors. The integration of DataFlux, a robust data quality tool, facilitates the validation process, ensuring that the extracted data meets predefined quality standards. Following validation, the standardization process is applied to ensure that data conforms to predefined formats and conventions. MDM Informatica, a leading MDM tool, plays a pivotal role in standardizing healthcare data, aligning it with industry standards and organizational requirements.