@harshach
Nothing here yet.
Nothing here yet.
Feb 5 · 5 min read · At Uber, we had over 300,000 datasets, and most of them were unowned. Engineers couldn't find the data they needed, and when they did, they had no way to know if they could trust it. Who owned this table? Where did the data come from? What did the nu...
Join discussion
Jan 12 · 7 min read · Metadata is the foundation of modern analytics and AI. When schemas change, new tables appear, or ownership shifts, those changes ripple immediately through dashboards, models, and pipelines. If metadata lags behind reality, teams lose trust and syst...
Join discussion
Oct 22, 2025 · 7 min read · Most data teams still spend hours chasing tables, fixing quality issues, or verifying reports, rather than analyzing data to drive business impact. The problem isn’t the value of data. It’s that it’s hard to find, understand, and trust across scatter...
Join discussion
Jul 23, 2025 · 13 min read · Organizations need deeper context about their data — not just for human data practitioners but also for AI agents and LLMs. Without this understanding, data practitioners make flawed assumptions, AI agents produce misleading recommendations, and LLMs...
Join discussion