Forbes contributors publish independent expert analyses and insights. The “exciting” things programmers like is making things happen — deep down, every programmer out there got their start because ...

Similarly to how XML became the well-known standard adapted by many software vendors for data exchange, Resource Description Framework (RDF) is going in the same direction for describing and ...

Most projects benefit from having a data model. This article gives an overview of the most common types. At its heart, data modeling is about understanding how data flows through a system. Just as a ...

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 and ...

As more organizations embrace big data and analytics to gain insight from extremely large datasets, the tools and systems used to manage data have grown, changed, and mul­tiplied. Instead of just ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Data modeling is the procedure of crafting a visual representation of an entire information system or portions of it in order to convey connections between data points and structures. The objective is ...

Organizations often force the DBA to take on the job of data modeling. That does not mean that DBAs are well-trained in data modeling, nor does it mean that DBAs are best suited to take on this task.