Everyone has probably learned by now that data is an inevitable part of the future claims management for decision support, automation and business development. But to work with data, it’s essential to know the difference between structured and unstructured data. We’re here to give you a quick data knowledge injection!
Let’s begin with the very basics of data. To organize data in a database, you need to use several different data models. Simplified, it is about storing data in tables, and the most used model is the relational model.
What is unstructured data?
Most data is unstructured or qualitative, meaning it has no fundamental structure and does not conform to any other model. Therefore, it cannot be gathered, stored, and organized in a database structure, since it doesn’t have a clear format. It is often made up of subjective opinions in text, that is, in fact, qualitative, but most analytics software can’t make use of it.
Some examples of unstructured data are: images, videos, medical records and any kind of scanned document.
What about structured data?
Structured data, also defined as quantitative data, is, as the name suggests, organized, which makes it easy for machine learning algorithms to decipher the data. Structured data has a clear structure, follows a particular order, and is easy to access for computers and living persons. Because of its characteristics, structured data is by far the easiest to use.
Take Google as an example. They use structured data online to understand a website’s information and gather general information about the site and topics. Structured data makes it easier for Google to classify the content on a specific page.
Some examples of structured data are: numbers, dates, and groups of words and numbers called strings.
Why do insurance companies need structured data?
Almost all data could be beneficial to companies. However, a lot of the data is unmeasurable, like a video. That is why structured data is so important, as you can easily draw conclusions from it. Structured data can be used both for AI and machine learning to give precise predictions about various aspects of your business.
In short: If you want to use data for analytic purposes or business predictions – the data needs to be structured. Claims management is a complex and expensive process where data has a considerable impact.
Mavera DSS enables you to collect structured data from every claim in a secure and compliant manner. From the data, it provides you with automated decision support and performance dashboards.
Book a meeting with us to learn more about how we can help you get structured.