A real-world AWS QuickSight playbook based on deploying ML models, modern BI pipelines, and protecting $8.3M in ...

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 ...

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 ...

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 ...

As a data engineering leader with over 15 years of experience designing and deploying large-scale data architectures across industries, I’ve seen countless AI projects stumble, not because of flawed ...

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 ...

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 ...