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. Even as large language models have ...

AI initiatives don’t stall because models aren’t good enough, but because data architecture lags the requirements of agentic systems.

At its heart, data modeling is about understanding how data flows through a system. Just as a map can help us understand a city’s layout, data modeling can help us understand the complexities of a ...

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 ...

Occasionally one may hear that a data model is “over-normalized,” but just what does that mean? Normalization is intended to analyze the functional dependencies across a set of data. The goal is to ...

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, ...

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 between ...

Dr. Chris Hillman, Global AI Lead at Teradata, joins eSpeaks to explore why open data ecosystems are becoming essential for enterprise AI success. In this episode, he breaks down how openness — in ...

NoSQL database systems continue to gain traction, but they are still not widely understood. There is more than one type of NoSQL database and a large number of individual NoSQL DBMSs. There are more ...