Common data types

1. Common data types

In this video, we will discover the ins and outs of some of the most common data types.

2. Importance of the data type

We'll often have to use different types of data to get a complete picture in an analysis. The data type mainly affects how to collect the data, how to store the data, and how to analyze the data. We need to make two main distinctions: whether the data is structured or unstructured and whether the data is qualitative or quantitative.

3. Structured vs. unstructured data

Structured data is data in tabular form, organized in rows and columns. Because it has such a strict structure, it can easily be read and used by a computer. It is typically stored in relational databases. Unstructured data, on the other hand, has no pre-defined structure. Because of that, more preprocessing is necessary before this type of data can be used in an analysis. Unstructured data is typically stored in document databases.

4. Examples of structured data

Structured data is the most recognizable type of data. It is likely what would come first in your mind when thinking about data. Spreadsheets, like Excel, are a common example. It consists of sheets of data arranged neatly in rows and columns, which can then be used for calculations.

5. Examples of unstructured data

Unstructured data has no pre-defined format and so can come in many forms. Common examples are images, videos, sound files, and texts like email, social media posts, or ratings.

6. Quantitative vs. qualitative data

The second important distinction is between quantitative and qualitative data. Quantitative data describes something numerically; it can be measured or counted, like the distance between your home and work. Qualitative data, however, describes something with categories that can be observed, like the color of your eyes. Unlike quantitative data, calculating statistics and analyzing qualitative data is more restricted. For example, we can calculate average length, but the average color would not make much sense.

7. Examples of quantitative data

If we were to describe ice cream quantitatively, for example, we could measure or count things like the number of ice cream scoops, the minutes before the ice cream starts to melt, or the length of the cone.

8. Examples of qualitative data

If, on the other hand, we would qualitatively describe ice cream, we could talk about the flavor of the ice cream, the color, or whether we want a cone or a cup.

9. Let's practice!

Time to put your new knowledge about data types into practice!

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