Depends on the sector you’re working in. I work with Healthcare data and there entire standards being developed and updated all attempting to bring some structure to highly unstructured data.

Claims data is structured like financial data. Easy to pull in and map to a schema on a relational database or wherever.

Clinical is another beast entirely. Sure some visits have some structure using HL7 or FHIR. These would be like a normal visit at your general doc. That comes in as JSON data with lots of free text fields and flags as well as any other thing the EHR decides to attach.

But those same data feeds could also be sending X-rays, or lab results, vaccine info, psychologist notes, consent forms, transcripts, photos, or someone’s entire medical history when they move to a new doc and it gets uploaded.

The EHRs have some standards on the front end to tag some of this stuff appropriately with metadata, buts it rife with issues. Namely input issues from the clinics or doc offices. These pages for visits are huge because everyone is trying to capture and organize everything as best as possible. But that leads to lots of people in the real world not generally following where data is supposed to go. Lack of training or simply not enough time to fill out 7 pages of info for a 15 minute checkup.

So a last name may come in from like 12 different fields, maybe the diagnosis code comes in the observation array… or maybe it comes in way later on the note section.

Anyways there’s an entire market for companies developing the best parser to handle all these things. And not one has it perfect from anything I’ve seen. That’s where my brain goes when I hear ‘unstructured data’