In this article, I will talk about the different types of data. So, as some of you might be aware, data can be broken down into different types. One such categorization which is very useful when you are building a machine learning pipeline is the following: structured data, semi-structured data, and unstructured data.
So What Is the Difference Between These Types of Data?
Structured Data
This term refers to data that is organized in a tabular format or in something like a relational database which organizes data in multiple tables which can then be joined together. So structured data presents the easiest type of data to work with. If your data is stored in an SQL database, for example, then most data scientists will find it pretty easy to access the database and then extract insights from the data. That being said, not all databases are created equal. Some databases might be organized in a very bad manner; other databases might be organized in a very easy-to-use manner. But all things being equal, structured data is easy to work with.