How have advancements in AI impacted your master data management strategy?

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Director of Data in Healthcare and Biotecha year ago

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.

Director of Dataa year ago

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.

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Feasibility5%

Efficiency impact35%

Financial impact14%

End-user interest41%

Executive interest2%

Don’t know

We don’t have any GenAI initiatives1%

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Analytics developers19%

Business analysts41%

Business consumers43%

Data analysts43%

Data engineers22%

Data scientists24%

Data stewards16%

Database administrators (DBAs)7%

Integration architects8%

ML and AI engineers14%

Elsewhere4%

Nowhere, we aren't adding new GenAI capabilities2%

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