Most organizations have a mix of structured data and unstructured data. It’s not easy to maintain structure for every document that enters the database or storage locations for a business, but structuring that information makes it easier to search through and easier to data mine.
The best most organizations can do is to use templates or file types like emails to make unstructured data into semi-structured data. So, which is which? How should you manage unstructured data, and how do you manage structured data as well?
Structured data and unstructured data
Structured information is stored in a standardized format or created in that format to be stored and accessed easily. It is usually found in the form of a spreadsheet or stored on an SQL database so that it can be retrieved when searched for. And it is quantified or categorized so that the data can be studied, analyzed, or easily monitored. Because of the rigid form and expectation of the information, this makes it easier to control. Privacy and security can be more easily maintained. And with strict parameters in a predetermined framework, there is less potential for inaccuracy.
Unstructured data is basically everything else. Text documents. Written documents. Social media posts. Satellite imagery and X-Rays. Videos and recordings. While this stored data can be listed by title or other fields and accessed via the list, the actual nature of the data (security footage for instance) doesn’t lend itself to complete structuring. Semi-structured data already makes itself readily searchable, accessible, and controllable in certain ways but not others.
Dealing with unstructured data
Usually, this will require manual processing or manual structuring, at least at first. After this, certain steps can be automated. Adding metadata to a document as you input it into the system lets you then look that document up by keywords, dates, or user at a later date. Document use can also be monitored and audited, data that itself can and should be stored in a structured way.
For written files that can’t be read by machine tools at all, Optical Character Recognition (OCR) all but reverses this condition. It does not put the text of a document into the same level of searchable, secure structuring as a spreadsheet, but it at least allows us to treat written files the same as typed files – in terms of search and access. This process can even become completely automated so long as the files have categorizing information in uniform locations.
Digital and online forms can have fields that allow for total control and structural utility. If the form type and processing number have a designated position the system recognizes, all of these documents can be filed by the right indexing software. In conjunction with OCR, and using automated metadata population, even physical forms can enter into the system with more structure.
Document control and unstructured/semi-structured data
Most data is unstructured. That’s not to say that it’s all messy. But it can’t easily be funneled into a database and secured in this way. What you can do instead is use tools meant to make it easier for the bulk of your data to enter the system en masse with automation for fast processing, metadata for easy lookups, workflows for sharing that data and using it daily, and encryption to secure your organization’s information. A document management solution covers all of these requirements in a single product or suite.