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

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results.

Modern vision-language models allow documents to be transformed into structured, computable representations rather than lossy text blobs.

Unstructured data refers to information that does not have a predefined data model or organized format, making it more challenging to store, process, and analyze compared to structured data. Unlike ...

Tabular foundation models are the next major unlock for AI adoption, especially in industries sitting on massive databases of ...

Artificial Intelligence (AI) is transforming industries by automating tasks and generating insights, but its true effectiveness depends on high-quality, relevant data. Structured data is the most ...

Unstructured data isn’t an asset by default — it’s a liability until CIOs govern, lifecycle and curate it for AI-ready value.

A sample of 4,615 adult patients were randomly selected from the Multiparameter Intelligent Monitoring in Critical Care (MIMIC-III) database. The structured data were obtained by queries of the ...

Allowing quality data in can lead to a better understanding of an organization. Here are 5 steps to improve your organization's data quality for unstructured data. Image: momius/Adobe Stock Finding ...

The Data Cloud has rightly been one of Salesforce’s biggest product focuses this year. As the company’s World Tour series of events hit New York yesterday, the latest news was that it will soon be ...