Data Types in Data Science

A quick guide on the differences between quantitative and qualitative data

There are a lot of engineers who have never been involved in the field of statistics or data science. But in order to build data science pipelines or rewrite produced code by data scientists to an adequate, easily maintained code many nuances and misunderstandings arise from the engineering side. For those Data/ML engineers and novice data scientists, I make this series of posts. I’ll try to explain some basic approaches in plain English and, based on it, explain some of the Data Science basic concepts.

Defining the type of variable you are working with is always the first step in the data analysis process. Later on, this makes it easy to determine which type of analysis is the most appropriate.

In its most general form, the data can be divided into quantitative and qualitative.

Quantitative, as the name implies, is a data type where numbers have a mathematical value, they indicate a quantity, amount, or measurement of a characteristic.