How have advancements in AI impacted your master data management strategy?
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In my opinion, Advancements in AI and related data field have significantly enhanced our Master Data Management (MDM) strategy by automating data quality, integration, and governance processes. AI algorithms help identify and resolve data inconsistencies, quality, duplicates, gaps, and inaccuracies more efficiently than traditional methods. Also, AI-driven analytics provide deeper insights into data usage patterns ( good actionable insights thru visualisation) , enabling proactive data stewardship and better decision-making.
We have also conducted a proof of concept by designing our first MDM solution using Microsoft Dataverse. This initiative aimed to address data consistency and quality issues within our Power Apps solutions. The implementation showcased how AI and Dataverse can work together to create a more agile, accurate, and scalable MDM system, ensuring high-quality enterprise data that effectively supports our business objectives.
In the lifesciences and pharmaceutical industry I have not seen a lot of advancement in MDM strategy leveraging AI. However, I would hope that a lot of data standardization can be achieved using AI. Will be interesting to see who leads the path in this space particularly.