Distributed database consistency models form the backbone of reliable and high-performance systems in today’s interconnected digital landscape. These models define the guarantees provided by a ...

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 ...

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 ...

One of the biggest challenges facing organizations today is making sure that the right information gets to the right people. It requires attention, diligence, and planning to ensure that data is used ...

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

It has been widely documented - data is growing at astronomical rates. The amount of data your organization has is less important than how the data is being used. Is data growth hindering your ...

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 ...

Sophie Bushwick: To train a large artificial intelligence model, you need lots of text and images created by actual humans. As the AI boom continues, it's becoming clearer that some of this data is ...