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

The quest for more training data has created a glut of low-quality junk data that could derail the promise of physical AI.

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 ...

The addition of Transformational Modeling, Tx, allows data teams to simplify, automate, and collaborate on their end-to-end data modeling workflows. SAN FRANCISCO--(BUSINESS WIRE)--SqlDBM, a leading ...

Most AI systems are trained on historical data. When conditions shift due to changing consumer sentiment, models trained on ...

If your are wondering how to handle large datasets and complex calculations in your spreadsheets. This is where MS Excel PowerPivot comes into play. PowerPivot is an advanced feature in Excel that ...

The healthcare system is faced with a tsunami of incoming data. In fact, the average hospital produces roughly 50 petabytes of data every year. That’s more than twice the amount of data housed in the ...

Uncertainty quantification (UQ) is a field of study that focuses on understanding, modeling, and reducing uncertainties in computational models and real-world systems. It is widely used in engineering ...

GitHub has introduced a significant update to its CodeQL engine, enabling developers to define custom sanitizers and ...

The Data Science and Modeling for Green Chemistry award aims to recognize the research and development of computational tools that guide the design of sustainable chemical processes and the execution ...