What is data modeling, and why does it break down? Fundamentally, data modeling involves arranging data in a structured way to improve accessibility and use for a range of applications and analyses.

Data models are used to represent real-world entities, but often have limitations. Avoid common data modeling mistakes for data integrity.

Data analytics have either been centralized or decentralized. Data mesh tried to fix that. The hub-and-spoke model goes further.

Better data annotation—more accurate, detailed or contextually rich—can drastically improve an AI system’s performance, adaptability and fairness.