Structured Data: Examples, Sources, And How It Works
Datamation, Friday, July 21,2023
Data falls into two categories: structured and unstructured. Structured data is a type of information that has been organized in a way that makes it easily searchable and readable by data analysis tools, while unstructured data includes content like videos, emails, and images-data with no internal identifier to help search functions recognize it. Your business likely deals with both types of data. This article looks closely at structured data, which is the backbone of data analysis.
What Is Structured Data? Types & Examples
Structured data, or quantitative data, is highly organized and readable by machine learning algorithms, making it easier to search, manipulate, and analyze. Structured data can include names, addresses, dates-fields that are recognizable and searchable by computers.
Compare this to unstructured data, which includes everything from social media posts to music files, emails, and images. It's estimated that unstructured data makes up between 80 and 90 percent of all data generated globally.
Despite making up a much smaller percentage of existing data, structured data is considerably more valuable, as it's much easier to handle and extract insights from.