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 ...

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 models are used to represent real-world entities, but they often have limitations. Avoid these common data modeling mistakes to keep data integrity. Data modeling is the process through which we ...

Database provider Couchbase has unveiled a comprehensive suite of model hosting and data processing capabilities for building, deploying and governing agentic AI applications. By bringing data and ...

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 ...

New semantic generators in Data Architect transform business definitions and relationships already captured in enterprise data models into semantic models and layers for AI, Microsoft Power BI, dbt, g ...

So-called “unlearning” techniques are used to make a generative AI model forget specific and undesirable info it picked up from training data, like sensitive private data or copyrighted material. But ...