This 12-part blog series is designed to answer this question by providing guidance on data modeling patterns for 12 common use cases. To help you get to a blog that can help you build now, the ...

Data modeling has always been a task that seems positioned in the middle of a white-water rapids with a paddle but no canoe. On one side of the data modeling rapids are the raging agilists who are ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

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 ...

First, institutions must ensure that synthetic datasets are continuously recalibrated against fresh, real-world evidence. The world moves, behaviors shift, economies cycle and disease patterns evolve.