July 15, 2025
Self-Service Data at AI Scale — An Open Agentic Architecture for the Enterprise
Promethium CEO Prat Moghe introduces a new agentic approach for self-service data at AI scale.
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November 12, 2025
The AI Insights Fabric: Why Enterprise Data Needs a New Architecture
Discover why current architectures can't deliver trusted AI insights at scale — and what the new AI Insights Fabric makes possible.
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November 1, 2025
The End of the Data Fabric vs Data Mesh Debate
The five-year architectural war is over — organizations implementing both approaches consistently outperform single-strategy implementations.
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September 9, 2025
Open vs. Closed Data Fabric: A Strategic Guide for Enterprise Data Leaders
Looking for an alternative to Microsoft Fabric? Promethium delivers instant, AI-ready answers from all your data—without the migration, lock-in, or complexity of OneLake and manual modeling.
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July 10, 2025
Data Answers — A Faster, Smarter Way to Enterprise Analytics
Discover Data Answers — a faster, more contextual way to deliver real-time insights. Learn how to get trusted, governed answers in minutes.
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July 3, 2025
The Missing Link In Your Modern Data Stack
Promethium is the missing link in your modern data stack — connecting your tools, context, and teams to deliver instant, trusted answers without rebuilding your architecture.
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June 13, 2025
If AI Is So Smart, Why Can’t It Understand Your Enterprise Data?
Most enterprise AI fails not because the models are wrong — but because the data architecture can’t deliver the right context, access, or speed.
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May 20, 2025
Unlocking Self-Service Data at AI Scale
A practical guide to overcoming the real-world roadblocks that prevent enterprise AI from delivering trusted, real-time insights.
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November 20, 2024
7 Use Cases for Data Fabric in the Modern Enterprise
A practical guide to how data fabric technology is transforming access, agility, and AI-readiness across the enterprise.
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May 10, 2024
Eckerson: Unifying Enterprise Data
A research-backed guide from Eckerson Group on bridging the gap between operational systems and analytics with a unified data fabric approach.
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