Unstructured data can be machine-generated as well, with examples including: IoT data: As the number of smart, internet-connected devices grows, so does the amount of data they create and collect.

Data scientists today face a perfect storm: an explosion of inconsistent, unstructured, multimodal data scattered across silos – and mounting pressure to turn it into accessible, AI-ready insights.

Studying these tables for insights is relatively simple and straight-forward for data scientists. Some data sources, though, lack predictable order, but this doesn’t mean that they can’t be ...

Visualization tools can support data from multiple sources and join or overlay the results, providing companies with a way to extract meaningful business intelligence from unstructured data.

For the study, Ponemon defined unstructured data as electronic information residing on file servers and NAS devices that is not stored in a database or in a document/content management system.