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 ...

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 ...

Microsoft Fabric expands as industry analysts reveal critical criteria enterprises need for evaluating AI-ready data ...

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, ...

Amazon Web Services's AI Shanghai Lablet division has created a new predictive model -- an open-source benchmarking tool called 4DBInfer used to graph predictive modeling on RDBs, a relational ...

We’re in a hinge moment for AI. The experiments are over and the real work has begun. Centralizing data, once the finish line, is now the starting point. The definition of “AI readiness” is evolving ...

The process of de-identifying test databases can be approached in a variety of ways, and we’re often asked how our approach differs as compared to others. In this article, we’ll explore how our ...

Vector databases are all the rage, judging by the number of startups entering the space and the investors ponying up for a piece of the pie. The proliferation of large language models (LLMs) and the ...

For a long time, companies have been using relational databases (DB) to manage data. However, with the increasing use of ...