We look at alternatives to relational databases that have emerged to help bring some structure to unstructured data and gain valuable insight by making it semi-structured.

The distinction between structured and unstructured data is important because automated reasoning, one of the pillars of Web 40.0, requires both kinds of data analytics.

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.

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

Digital Reef plans to manage unstructured and semi-structured data, that is data not already managed by database management systems, by helping large enterprises deal with key business issues that ...

As with structured data, simply collecting unstructured data won’t get you the insights you need. Even unstructured data has to be properly organized.

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

Having access to this data gives you valuable insight into where your company is doing well or falling short, empowering you to take steps to address bias within your organization.

The data collected by most security tools, such as firewalls and antivirus software, is structured — that is, organized in an easily searchable, relational database.