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

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

As companies rely more heavily on real-time analytics and AI-driven tools, data engineering is evolving into a role that ...

Discover the key differences between Data Science, Data Engineering, and AI. Learn about their unique roles, technical ...

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 ...

Dr. Douglas Orellana, vice president of Intelligent Systems Engineering, ManTech With the emergence of Industry 4.0—the realization of digital transformation—many feel that engineering organizations’ ...

Today’s data landscape presents unprecedented challenges for organisations, due to the need for businesses to process thousands of documents in numerous data formats. These, as Bogdan Raduta, head of ...

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 ...

Bloomberg’s Data Technologies Engineering team is responsible for the data collection systems that onboard all of the referential data that drive the company’s applications and enterprise solutions.

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 ...