Most enterprise data lives outside databases. Here's why that's holding AI back — and how connecting context can change it.

Enterprises face key challenges in harnessing unstructured data so they can make the most of their investments in AI, but several vendors are addressing these challenges.

With the exponential growth of data, the pace of innovation and evolving governance needs, the concept of data gravity becomes more pressing than ever. Enterprises face the critical decision of ...

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data ...

Forbes contributors publish independent expert analyses and insights. I track enterprise software application development & data management. Information, without order, is chaotic. Attempting to work ...

Data scientists today face a perfect storm: an explosion of inconsistent, unstructured, multimodal data scattered across silos – and mounting pressure to turn it into accessible, AI-ready insights.

What’s the best way to store, search, and analyze content not based on their technical characteristics but on their meaning? The volume of data being created today is truly staggering. IDC projects ...

In this TechRepublic exclusive, a COO states that successful AI initiatives must have the right unstructured data at the right time. Then, she details the proper unstructured data preparation for AI.

We talk to Nasuni founder and chief technology officer (CTO) Andres Rodriguez about the characteristics needed from storage to make optimal use of unstructured data in the enterprise, as well as the ...