Let's talk about the most common categories of data you see in analysis today. As you know data is everywhere and it can be stored in lots of ways. most of them will be categorised into 2 types.
- Structured Data
Organised in a certain format e.g. columns and rows. - Unstructured Data
Not organised in easy way to digest it.
Example of use of structured data is when you check how much of the calories 2 foods have and decide which one to choose based on the data. And another example for unstructured data is when you go through google reviews and decide whether you should purchase that item.
Characteristics of Unstructured Data
- Mostly qualitative data
- Hard to search
- Provides more freedom when analyse
- Cannot be put in rows and columns
- Ex: social media comments, texts, images, videos, audio
Summary
Unstructured data is hard to analyse as it is not organised in any easily identifiable manner, but the thing is there is more unstructured data in the world compared to structured data.
Recent advancements in artificial inteligence helps unstructured data analysis, but then we need to make sure the algorithms used for that analysis is inclusive and not biased as this will affect the result and your solution for the problem.