Data engineering is the gritty, often unglamorous work that underpins every AI model, every dashboard, and every strategic data driven decision. For years, we treated our data lakes like giant, messy ...

Imagine it’s 3 a.m. and your pager goes off. A downstream service is failing, and after an hour of debugging you trace the issue to a tiny, undocumented schema change made by an upstream team. The fix ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...

For decades, organizations have approached data architecture with a monolithic mindset—centralized platforms, complex codebases and rigid structures. While these systems were built with the noble goal ...

In today’s AI gold rush, the startups that win aren’t just the ones with the best models—they’re the ones with the strongest data foundations. As AI-native companies race to productize intelligence, ...

Though the AI era conjures a futuristic, tech-advanced image of the present, AI fundamentally depends on the same data standards that have been around forever. These data standards—such as being clean ...

KDNuggets, a community site for data professionals, ranked “We Don’t Need Data Scientists, We Need Data Engineers,” by Mihail Eric, a venture capitalist, researcher, and educator, as its top story of ...