The intersection of the COVID-19 pandemic and analytics has been in focus almost since the pandemic began. Organizations like Johns Hopkins Center for Systems Science and Engineering (CSSE), the New ...

Over the years, we've seen a couple of different organizational models for delivering analytics to the business. While both models have their advantages, each model has some severe drawbacks that make ...

Conventional data management systems are fundamentally ill-suited for the world of data as it exists today. These systems, based with few exceptions on the relational data model, are broken because ...

Disparate BI, analytics, and data science tools result in discrepancies in data interpretation, business logic, and definitions among user groups. A universal semantic layer resolves those ...

Metadata is increasingly driving semantic data modeling, said Suresh Nair, New York-based vice president and chief architect, financial services, at IT processing services company Mphasis, who was ...

Sometimes, you can enter into a technology too early. The groundwork for semantics was laid down in the late 1990s and early 2000s, with Tim Berners-Lee's stellar Semantic Web article, debuting in ...