Data architecture is a critical part of architecting a highly scaled, highly available, globally accessible, modern application. Mistakes in your data architecture can cause issues with scaling ...

Who needs rewrites? This metadata-powered architecture fuses AI and ETL so smoothly, it turns pipelines into self-evolving ...

The evolving landscape of data architecture has shifted in the past two years with the arrival of AI capabilities -- fundamentally changing how organizations evaluate, justify, and implement their ...

Data architecture, however, spans the organization and takes a high-level, holistic view, whereas data modeling focuses on specific systems or business cases.

“Data architecture is many things to many people and it is easy to drown in an ocean of ideas, processes and initiatives,” says Tim Garrood, a data architecture expert at PA Consulting.

Data collection, storage, visualization, and data analytics serve as pieces of the puzzle making up the open data architecture. About the author: Anais Dotis-Georgiou is a Developer Advocate for ...

Advance the data management architecture to support generative AI capabilities. Evolve data infrastructure to support multiple architecture patterns. Data storage choices will have a long-lasting ...

Data Architecture Best Practices. Building a modern data architecture requires careful consideration of all the data technologies utilized to efficiently meet your enterprise’s commercial strategy.

But first things first mandate that the right data architecture be put in place to fully enable AI. While data lake solutions help accelerate this process, the right architecture cannot be bypassed.

A data architect defines “how the data will be stored, consumed, integrated and managed by different data entities and IT systems, as well as any applications using or processing that data. ...