Data modeling best practices give structure and direction to an organization's data. Read more about data modeling now.

Most projects benefit from having a data model. Read this article for an overview of the most common types.

Even as large language models have been making a splash with ChatGPT and its competitors, another incoming AI wave has been quietly emerging: large database models.

Amazon said through the new model, 4DBInfer, the company aim to accelerate research on graph-centric predictive modeling for relational databases by providing a unified, fully open-sourced framework.

The real value comes when graph databases and knowledge graphs are integrated, said Gnau. “In a multi-model platform, graph and semantic modeling capabilities work together to provide both structure ...

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...

Enterprises are creating huge amounts of data and it is being generated, stored, accessed, and analyzed everywhere – in core datacenters, in the cloud distributed among various providers, at the edge, ...

Using PowerPivot for Data Modeling When you use PowerPivot, you can import millions of rows of data from various sources such as databases, spreadsheets, and online services. This capability is ...

Large language models evolved alongside deep-learning neural networks and are critical to generative AI. Here's a first look, including the top LLMs and what they're used for today.

Stiff competition from database rivals has forced Oracle to shift its strategy for its databases business in favor of developers, who could offer the company a much-needed impetus for growth.