By promoting data stewardship and ownership by domain experts, using a common set of tools and semantic definitions, your entire organization will be empowered to create data products at scale.

Lastly, unlike relational data models that require us to anticipate all the data we will need to accommodate in advance, the semantic data model can be defined as the data arrives. This allows new ...

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 ...

Industry-specific semantic models are readily available for use with any BI tool, offering immense value to companies seeking to leverage data modeling in their operations.

Adopting a universal semantic layer carries many benefits in data accuracy and consistency—and in getting AI projects off the ground—but it requires change management.

Data and data standards in semantic web To obtain a thorough comprehension of the semantic web technology, the same information provided in the earlier XML example (Fig. 1) has been described in ...

Element Analytics Inc., maker of a semantic data platform for use in industrial settings, today announced the availability of its Unify data management platform on Microsoft Corp.’s Azure ...

BOSTON, April 27, 2023 — AtScale, a leading provider of semantic layer solutions for modern business intelligence and data science teams, today announced new capabilities within its semantic layer ...