Unstructured Data and its Importance

Unstructured data, which includes various types of files like imagery, audio, 3D models, documents, and emails, is extensive and valuable. Despite the name, unstructured data actually possesses a certain level of structure, with known schemas and file formats. However, the term "unstructured" aims to differentiate it from structured, modern data stacks. Metadata plays a crucial role in managing unstructured data, with first-order metadata being the basic metadata obtained directly from file headers, providing initial information about the file contents. Second-order metadata involves reading the actual data within the file, such as performing object detection on an image or extracting terms from a document. Finally, third-order metadata refers to inferences and contextualization, where connections are made between different datasets and databases. Machine learning and knowledge graphs are often used to achieve these higher levels of metadata. The ability to generate insights and link data from unstructured sources is of great interest, with applications in various industries like geospatial, media, and property inspection.