Data architecture vs. data modeling. According to Data Management Book of Knowledge (DMBOK 2), data architecture defines the blueprint for managing data assets as aligning with organizational ...

Architecting modern applications is a tough job, and architecting a solid data model for modern applications is one of the toughest, yet most important, parts of a modern application architecture ...

A novel approach from the Allen Institute for AI enables data to be removed from an artificial intelligence model even after ...

defining the data architecture framework, standards, and principles, including modeling, metadata, security, reference data such as product codes and client categories, and master data such as ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis ...

The Components of a Modern Big Data Architecture. While there are several data architecture models consisting of a range of components, fundamentally, the most straightforward data architecture model ...

According to DAMA International’s Guide to the Data Management Body of Knowledge, enterprise data architecture typically consists of three major sets of design components. First, an enterprise data ...

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.

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

A guide to the 10 most common data modeling mistakes Your email has been sent Data modeling is the process through which we represent information system objects or entities and the connections ...