Probabilistic graphs and uncertain data analysis represent a rapidly evolving research domain that seeks to reconcile the inherent imprecision of real-world data with robust computational models. By ...

The analysis of cancer biology data involves extremely heterogeneous data sets, including information from RNA sequencing, genome-wide copy number, DNA methylation data reporting on epigenetic ...

Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 53, No. 2 (2004), pp. 249-260 (12 pages) ...

The relentless march of digital technology (and I have to admit I’m getting really tired of saying that) assures that all organizations will adopt AI in some form to stay competitive. The accumulative ...

How would you feel if you saw demand for your favorite topic — which also happens to be your line of business — grow 1,000% in just two years’ time? Vindicated, overjoyed, and a bit overstretched in ...

Graph databases are gaining attention as enterprises work on their next-generation artificial intelligence (AI) applications. While still a bit of an outlier, graph-oriented databases continue to find ...

Graph databases are amazing, but the knowledge graph is in your data already. That's the key message Siren has been advocating, and today it raised $10 million in Series A financing led by Atlantic ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. As enterprises continue to navigate the complexities of digital transformation, connected ...

The two terms data analysis and data visualization seem to have become synonymous in everyday language in the wider data community. Numerous job adverts focus on data visualization skills while not ...

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 ...