Empromptu's "golden pipeline" approach tackles the last-mile data problem in agentic AI by integrating normalization directly into the application workflow — replacing weeks of manual data prep with ...

This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...

Silent schema drift is a common source of failure. When fields change meaning without traceability, explanations become ...

Mukul Garg is the Head of Support Engineering at PubNub, which powers apps for virtual work, play, learning and health. In my journey through data engineering, one of the most remarkable shifts I’ve ...

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 ...

What if you could future-proof your career by stepping into one of the most in-demand tech roles of the decade? As companies increasingly rely on data to drive decisions, the role of a data engineer ...

What’s the difference between a data engineer and a data analyst? Data isn’t much good without people who know how to collect it, shape it, and explain what it means. That’s where data engineers and ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. In this episode, Thomas Betts chats with ...