The process of de-identifying test databases can be approached in a variety of ways, and we’re often asked how our approach differs as compared to others. In this article, we’ll explore how our ...

A guide to the 10 most common data modeling mistakes Your email has been sent Data modeling is the process through which we represent information system objects or entities and the connections between ...

The Covid-19 pandemic reminded us that everyday life is full of interdependencies. The data models and logic for tracking the progress of the pandemic, understanding its spread in the population, ...

Sparse data can impact the effectiveness of machine learning models. As students and experts alike experiment with diverse datasets, sparse data poses a challenge. The Leeds Master’s in Business ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Data mesh is a hot topic in the data and ...

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, ...

Adobe, Microsoft and SAP have started one data initiative; AWS, Genesys and Salesforce another. Which will endure the test of time? Just days before Dreamforce, Salesforce's annual user conference ...

It’s been a huge 12 months for data and models. From the emergence of generative artificial intelligence (GenAI) tools such as ChatGPT in late 2022 to the ever-increasing reliance on machine learning ...