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Simple understanding of Dimensions & Measures


" How is your DAY ?" is a simple question, and each person has different answers.

My DAY is GOOD.

My DAY is BETTER.

My DAY is BAD.

My DAY is WONDERFUL.

My DAY is the WORST. etc.

Each person describes a DAY with different Adjectives(Moods), an independent variable. As we talk about DAY, it depends on these adjectives(independent variables) stated.

Here, DAY we can count thus it is a MEASURE (which is quantifiable) and moods are qualities that can be taken as DIMENSION.



Figure 1: Mood Tracker for 30 days with different moods of one person.

DIMENSION

MEASURE

Qualitative Data

Quantitative Data

Dependent variable

Independent variable

Splits up the data set into different categories to reveal different levels of detail in the data

A data set can be aggregated in some way, such as a sum or an average.

It is something that can be split and measured in distinct groups.

It is something that can be collected, counted, or combined in some way to return a single value.

Eg: Dates, Names, Geographical Data, Moods etc.

Eg: Days, Numeric values, anything countable etc.

We often get easily get confused with dimensions and measures. Since all the dimension fields are blue and the measure fields are green when we first load the dataset.


Converting measures into dimensions or dimensions into measures


Sometimes, Tableau automatically classifies a field as a dimension even though you want to aggregate it and sometimes Tableau might classify something as a measure even though you intend to split up the view with it. That is not a worry as we can easily convert dimensions into measures and vice versa.

Converting from measure to dimension can easily be done in Tableau but they will affect your visualizations and filters but converting may give you a better visualization than your initial one though so it is encouraged to try out which combination of these parameters yields the best results with utmost care.








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