While the core principles of data modeling remain unchanged, the landscape has split into two distinct needs: enterprise-level precision for governance and modern stack collaborati…
Many enterprises are struggling to achieve AI success because they rely on inefficient, manual data delivery models that result in significant waste and rework. However, new Omdia …
Many manufacturing AI initiatives are failing because companies are investing in advanced technology without first establishing a governed, integrated, and trustworthy data foundat…
This article argues that a successful AI strategy *requires* a robust data strategy, specifically one centered around a data marketplace. While building trusted data products is im…
This article argues that a data platform (like a data warehouse or lakehouse) is *not* enough for successful AI implementation. While data platforms store and process data, a separ…
This article argues that treating data as a product – with clear ownership, governance, and measurable ROI – is key to unlocking the true value of data and AI investments. Organiza…
This article argues that agentic AI is poised to revolutionize data management within months, automating tasks like policy enforcement and data provisioning. However, successful im…
This article highlights a shift in data management towards “data products”: packaged, curated, and governed data sets designed for specific business outcomes and AI applications. T…