When most people hear “observability,” they think of on-call rotations, alerts and dashboards for SREs. That narrow view is ...

Your AI isn't broken, your data context is; you need solid data engineering to bridge the gap between a smart model and a ...

Recent work under the INTEND project and the paper " Intent-Based Data Operation in the Computing Continuum " points in the ...

Effective data modeling enables value creation, efficiency gains, risk reduction, and strategic alignment in an environment of uncertainty and disruption. At Data Summit 2026, Pascal ...

Model-based systems engineering (MBSE) has been around for a while, but it continues to gain ground in engineering projects ...

A former Snowflake data scientist who refined multi-billion-dollar forecasts is now building AI models that outperform Claude ...

Data modeling tools play an important role in business, representing how data flows through an organization. It’s important for businesses to understand what the best data modeling tools are across ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

Just because your firm can use your existing data for AI risk modelling doesn’t mean you should. There’s a perception that AI can create accurate predictions based on any data set. That’s not always ...