Data modeling, at its core, is the process of transforming raw data into meaningful insights. It involves creating representations of a database’s structure and organization. These models are often ...

Google wants Gemini, its family of generative AI models, to power your app’s databases — in a sense. At its annual Cloud Next conference in Las Vegas, Google announced the public preview of Gemini in ...

Forbes contributors publish independent expert analyses and insights. I write about the economics of AI. When Snowflake announced its $250 million acquisition of Crunchy Data two weeks ago at its ...

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 ...

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 ...

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 ...

Vector databases and search aren’t new, but vectorization is essential for generative AI and working with LLMs. Here's what you need to know. One of my first projects as a software developer was ...

This article was written by Bloomberg Intelligence senior industry analyst Mandeep Singh and associate analyst Robert Biggar. It appeared first on the Bloomberg Terminal. AI’s shift to inference at ...

As businesses shift toward smarter digital infrastructures, the database landscape is rapidly evolving. Siva Prasad Nandi, a researcher in cloud-native technologies, explores the rise of serverless ...

In an era where artificial intelligence (AI) and machine learning (ML) are driving unprecedented innovation and efficiency, a new class of cyber threats has emerged that puts sensitive data and entire ...