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 ...

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 ...

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 ...

With the ongoing rapid increase in both volume and diversity of 'omic' data (genomics, transcriptomics, proteomics, and others), the development and adoption of data standards is of paramount ...

The demand for data continues to grow from inside and outside every organization and from machines now, too. However, having a surfeit of data is not enough. Organizations must solve the complex ...

Together with Snowflake, Sigma and other industry leaders are driving a new open standard for semantic data, ensuring organizations can define metrics once, govern centrally, and analyze everywhere ...