Implementing AI in healthcare isn’t just about choosing the right tools—it’s about making them work in the real world.

And technology can assess data—structured and unstructured—far more quickly and accurately than humans ever could, which means lower spend and reduced risk for the organization.

The untapped potential intelligence within unstructured content is driving new practices, new technologies and new roles.

In the dynamic world of data science, the conversion of unstructured data into structured data is a key process. This transformation is crucial for enabling more efficient data analysis and ...

In this TechRepublic exclusive, a COO states that successful AI initiatives must have the right unstructured data at the ...

What we're really doing is designating our data as structured or unstructured. Let's start with structured data, which is really data that is organized in a structure so that it is identifiable.

Quantzig breaks down the distinct differences between structured and unstructured data in its recent article.

It’s time to put unstructured data in the spotlight. Having the ability to process unstructured data should be an integral part of your business, no matter what kind of business you are.

The differences between structured and unstructured data mean that traditional database systems and modern AI database systems handle information in different ways.

Unstructured data — information that doesn’t follow conventional models or fit into structured database formats — represents more than 80% of all new enterprise data.