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 ...

Most modern data architecture layers utilize all or some of the following components: Data sources are fundamental to any data architecture. Sources can be anything from relational databases such as ...

A universal semantic data layer is a single business representation of all corporate data aimed at helping users access data using common business terms via the BI and analytics tools of their choice.

A modern semantic layer leverages data virtualization to enable new data landing in your data warehouse to be query-able by your BI tool immediately, regardless of size. Performance and scale ...

Data scientists today face a perfect storm: an explosion of inconsistent, unstructured, multimodal data scattered across silos – and mounting pressure to turn it into accessible, AI-ready insights.

A semantic layer resolves discrepancies between different naming conventions, formats and structures used in different storage locations including cloud warehouses, data lakes or on-prem RDBMS.

Conducted by the DBP Institute, a data and analytics research firm, the report quantifies the business impact of using a semantic layer for a company’s business intelligence (BI) and artificial ...

First, there was a data warehouse – an information storage architecture that allowed structured data to be archived for specific business intelligence purposes and reporting. The concept of the ...

The pace of innovation in data analytics and artificial intelligence (AI) is breathtaking. New use cases and possibilities emerge minute by minute. Around the world, organisations of all ...