Structured vs unstructured data – it’s a common way of categorising things. But it’s not quite that simple. Although structured data is easy to grasp, the world of unstructured data and its ...

Unstructured data is complicated compared to working with structured data - Finding the insight buried within unstructured data is challenging. It requires a high level of technical and analytics ...

Some data sources lack predictable order, but this doesn’t mean they aren't useful. Some AI scientists specialize in making sense of this unstructured data.

As a team, we’re all working on data. But we think and operate in separate orbits because structured and unstructured data live in different systems and provide different insights.

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.

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.

Unstructured data is data that isn’t organized in a way that can’t be instantly analyzed by a person or computer (think written surveys, videos, photos, emails and so on).

Unstructured vs. Structured Data Unstructured data populates the world around us. Everything we do or say is replete with data points that can be analyzed and used, from voice messages and emails ...