Insights on data governance, AI governance, data architecture, and responsible AI. By Vikas Pratap Singh.
A practical framework for enterprise AI governance that maps NIST AI RMF, EU AI Act risk tiers, and SR 11-7 into a unified operating model with clear decision rights, risk classification, validation processes, and monitoring capabilities.
A critical analysis of Uber's five-system data quality ecosystem -- DQM, D3, UDQ, Databook, and DataCentral -- examining what is genuinely innovative, what is standard practice in disguise, and which patterns are worth adopting at any scale.
Why dominant data governance maturity models like CMMI DMM, DCAM, and Gartner measure documentation completeness instead of governance effectiveness, and a practical outcome-driven framework built around decision rights, data literacy, and measurable business impact.
Essays on thinking clearly, living intentionally, and building a career worth having.
Get new articles on data governance, AI, and engineering delivered to your inbox.
No spam. Unsubscribe anytime.