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No Data, No Modernization, No AI
In the early stages of the generative artificial intelligence inflection, the technology sector rallied around a fundamental operational ...
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How Complete Data Ecosystem Visibility Unlocks Modernization at Scale
Global enterprises face a “black box” of legacy complexity. Decades of business rules, data transformations, and critical logic are buried ...
Using AI for legacy data modernization? Don’t fall into this trap
Brain Blog Post for Next Pathway by Eric Newcomer If the future of applications is in genAI, then the future of data for AI is in the ...
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Five Reasons why Next Pathway is Better than a Box of Consultants for Legacy Data Migration
BrainBlog for Next Pathway by Jason Bloomberg In the late eighteenth century, a chess-playing automaton called the Mechanical Turk was a ...
Accelerating the AI Data Cloud: The Automated On-Ramp for the New Industrial Era
At GTC 2026, the global enterprise timeline was reset. We are entering the largest infrastructure buildout in history, a reinvention of the ...
Designing the four pillars of AI readiness: Data platforms, pipelines, compute and governance
Modernizing an enterprise is an architectural challenge that cannot be solved by simply layering new technology over old foundations. While ...
The $1 Trillion Infrastructure Cycle: Why AI Factories Stall At The Legacy Gate
In a recent Forbes Technology Council piece, I described the Agentic Gap as the distance between what AI systems could achieve and what ...
Why Your Informatica-to-Snowflake Migration is the Strategic Anchor of AI Success
For many enterprises, ETL workflows, like Informatica PowerCentre, were once the architectural backbone of their data integration strategy. ...
From Legacy Data Warehouse to Modern Data Lake An AI‑First Migration Strategy
For decades, the legacy data warehouse was the architectural anchor for enterprise reporting. It was designed for a world of structured ...