Extracting and analyzing relevant medical information from large-scale databases such as biobanks poses considerable challenges. To exploit such "big data," attempts have focused on large sampling ...

This is a graduate-level course on theoretical aspects of Big Data. We will examine algorithms and data structures for dealing with massive data sets. We will discuss such topics as streaming ...

As big data takes a larger role in healthcare analytics, healthcare organizations may come to rely on algorithms, but some experts are questioning whether the algorithms should be overseen. A new ...

We live in the era of big data. The huge volume of information we generate daily has major applications in various fields of science and technology, economy and management. For example, more and more ...

The history of the social sciences has included a succession of advances in the ability to make observations and carefully test hypotheses. The compilation of massive data sets, for example, and the ...

Matt Calkins argues that companies should protect their data by running their artificial-intelligence algorithms in-house (“Don’t Let AI Steal Your Company’s Data,” op-ed, June 29). This ignores that ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

Chief Business Officer at Cognyte, head of Cognyte’s product, global R&D, business units, and go-to-market strategy. Our world has become increasingly digital. The pandemic that drove the world ...