Data management usually becomes interesting when something stops working—when a report looks right but tells the wrong story, or when AI succeeds in a lab and collapses in production. I work at the intersection of data quality, metadata, and governance as lived disciplines shaped as much by incentives and organizational habits as by technology. My background spans data analytics and data science, quality engineering, and enterprise data management, with information quality as the throughline. I’ve led large-scale data quality and metadata initiatives in complex enterprises, and my academic work examines information quality and data governance as socio-technical systems—especially as organizations push harder into AI-driven decisions.
Blog: https://medium.com/@tonymazzphd/
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