Data Digest
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The $25 Million Reason Georgia-Pacific Rebuilt Its Data Foundation
In a paper mill, every hour of downtime carries a steep price tag, with tens of thousands of dollars lost the moment a machine goes offline. To protect against that risk, site managers do exactly what sound operational logic dictates: they maintain robust inventories of spare parts. It's a responsible decision made at the local level, repeated across numerous manufacturing sites nationwide.
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Alation AI Labs
Your Context Layer Is Already Wrong
The hardest problem in enterprise AI is not giving agents context. It is keeping that context current as the business changes underneath it.
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Mark T. Nelson On Why AI Hasn't Changed The Fundamentals Of Building Great Software
If code is nearly free to generate, why are so many AI products still mediocre? That's the question at the center of a conversation between host Satyen Sangani and Mark Nelson, Venture Partner at Madrona and former CEO of Tableau,¹ on the season four premiere of AI Radicals.
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AI Failure Analysis: How to Diagnose What Went Wrong and Fix It
An AI agent doesn't fail the way software fails. A broken API throws a 500 error. A bad script crashes with a stack trace. An AI system does something worse: it gives you a fluent, confident, completely wrong answer, and nothing about the output tells you that. The number looks plausible. The reasoning reads clean. Everyone downstream believes it, right up until the moment a customer, an auditor, or a board member catches something that doesn't add up.
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How To Make Data AI-Ready: A Simple Checklist
Gartner predicts that through 2026, organizations will abandon 60% of AI projects unsupported by AI-ready data¹ — and a Gartner survey of over 1,200 data management leaders found that 63% either lack the right data management practices for AI or aren't sure they have them¹. The problem often isn't the AI model. If data is incomplete, outdated, hard to find, or missing context, even advanced AI tools produce poor answers.
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Choosing an AI Operating System for Enterprise Teams: What You Need to Know
An AI operating system (AIOS) is the layer that connects an enterprise's data, business context, AI agents, and governance so that AI stays accurate after the pilot ends, not just during the demo. This checklist gives IT and data leaders seven concrete questions to put to any AIOS vendor, built around the one thing most evaluations skip: whether the system gets more accurate over time, or quietly decays the day it ships.
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What Is A Knowledge Graph? A Plain-Language Guide For Data And AI Leaders
A knowledge graph is a business model: an ontology of what things exist and how they connect, populated with your real, governed data. It's the fix for a specific, well-documented failure mode: Gartner predicts that through 2026, organizations will abandon 60% of AI projects unsupported by AI-ready data.⁷ Usually, it isn't the model that's the problem — it's that the data underneath has no explicit structure for the model to reason over.
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Metadata vs. Context: What's the Difference and Why It Matters for AI
Most enterprises have spent the last decade building metadata infrastructure: data catalogs, glossaries, lineage graphs. Then they deployed AI agents on top of that investment and got confidently wrong answers anyway.
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What Is Intelligent Data Management? A Definitive Guide for the AI Era
Intelligent data management is the use of AI agents, active metadata, and automated governance to continuously catalog, contextualize, and act on enterprise data — keeping it accurate, trusted, and ready for both people and AI systems to use.
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The Alation Podcast Is Back: Introducing AI Radicals
Four seasons ago, we started a podcast to talk about data culture: how organizations actually change the way they work with data, one stubborn habit at a time.
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Alation Named Customers' Choice in Two 2026 Gartner Voice of the Customer Reports
Alation has been named as a Customer's Choice in the 2026 Gartner Voice of the Customer for Metadata Management Solutions1 and Voice of the Customer for Data and Analytics Governance Platforms2, with a 99% willingness-to-recommend rate, the highest of any vendor in the Data and Analytics Governance Platforms market.
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