A closely related term is data modeling. Both data architecture and data modeling aim to bridge the gap between business objectives and technology. Data architecture, however, spans the ...

While both data architecture and data modeling seek to bridge the gap between business goals and technology, data architecture is about the macro view that seeks to understand and support the ...

Data modeling tools play an essential role in ... modeling capabilities that support Model Driven Architecture and Standards and Model Patterns. Excellent support for business glossaries, detailed ...

Open source in-process OLAP system launches rival to Iceberg and Delta Lake table format, and more With a combined market ...

Fundamentally, data modeling involves arranging data in a ... making it difficult for centralized architecture teams to keep up with the domain-specific needs of different workgroups.

A headless data architecture means no longer having to coordinate multiple copies of data and being free to use whatever processing or query engine is most suitable for the job. Here’s how it works.

Until recently, there was no alternative to this segregated data architecture ... rushing an AI model into development without a strong data foundation. But complex data pursuits like generative ...