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.

For example, new systems are increasingly capable of analyzing unstructured data, and aggregating all of the relevant data points into a unified whole. What does this mean for privacy?

An unstructured data stream is one that is not actively managed by a transactional system, for example, data that does not reside in a relational database management system.

Data that falls outside of this scope has been referred to as unstructured data. Common examples of unstructured data include word processing documents and spreadsheets.

Examples of Unstructured Data: Emails: Emails contain free-form text, attachments, and metadata like sender and receiver information, making them a common example of unstructured data.

Examples of Unstructured Data: Emails: Emails contain free-form text, attachments, and metadata like sender and receiver information, making them a common example of unstructured data.

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.

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.

Examples of Unstructured Data: Emails: Emails contain free-form text, attachments, and metadata like sender and receiver information, making them a common example of unstructured data.

Komprise works with storage vendors to add unstructured data management to data which stretches across multiple vendors.