AI doesn’t have a data problem. It has a navigation problem.
The article argues that enterprise AI success depends less on acquiring more data or larger models and more on implementing a "navigation layer" of business context to ensure data …
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Data Operations
23 articles · Page 2 of 2
From data access to data empowerment: why AI changes the data product equation
Many organizations struggle to derive value from data because their existing datasets are not designed for practical use, leading to inefficient, manual preparation processes. To b…
Snowflake heist: How to crack the code on Snowflake ROI
To maximize Snowflake ROI, organizations must prioritize proactive architectural design and preparation rather than relying on reactive cost-cutting. By implementing precise data m…
The data modeling generation gap: Why teams are rethinking their tooling strategy
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…
AI ambition is outpacing data reality and the gap is getting expensive
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 …
AI in manufacturing isn’t failing. Your data is.
Many manufacturing AI initiatives are failing because companies are investing in advanced technology without first establishing a governed, integrated, and trustworthy data foundat…
How a data marketplace unlocks the value of trusted data products
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…
Your data platform isn’t your data strategy: Why “manage it later” is the lie that breaks AI
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…
Why data products belong on the P&L — and how to make them pay
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…
Agentic AI needs a foundation you build—not a tool you buy
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…
Building trusted data products at speed & scale with AI in 2026
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…