Unstructured vs semi-structured data: Order from chaos
Summary
And brings benefits to organisations that want to gain value from often very large stores of documents, images, sound files, video, social media posts, and so on. They are easy to use, by everything from large-scale enterprise applications to machine learning tools, but can be limited in how they are accessed and used and can be relatively onerous to maintain and to change once initially configured. YouTube does this to ensure copyright on music is not contravened when you upload a video, for instance, so these types of data can be tagged with new metadata-based, algorithm-based interrogation, should an organisation wish to throw compute at it. The big advantage of being able to put unstructured data into some form of semi-structured format is that it enables a range of use cases to emerge, such as analytics to spot consumer behaviour, market trends, sentiment analysis. A photograph of delivered item would be unstructured data, but metadata from the image file could be combined with geo-tracking information from delivery vehicles in a business intelligence tool.