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Understanding Dimensions, Measure and Attribute in Tableau

When you open Tableau and load a data set ,Tableau it self assigns few data fields as Dimensions and few others as Measures depending on type of data the fields has.

Data fields can be Date, string, integer etc. where as role for that is whether it is Discrete Dimension or Continuous measures.


Dimensions: Dimension is something like on which view you are going to build your chart .

For example Dimensions can be geographical data, date, names etc.. which reveals a lot about your data.

Dimension can define the level of details in the view.


Measures: Measures contains mostly numeric or quantitative values like which you can measure .

For example you can measure profit, sales, patient visits count etc. Measures can be aggregated.


Discrete and continuous Measures:

Tableau represents the data depending on whether they can measured continuously or discrete.

Discrete is represented in BLUE and Continuous in GREEN.

Blue Dimension and measures are discrete means individually, separate and distinct .

These values are finite.


Green Dimensions and measures are continuous means which is whole ,no interruption.

These values are infinite.

For example when we consider superstore data set ,

Product name -Discrete Dimensions

Year -continuous Dimensions

Profit -Discrete and continuous


Examples:

In the example below, because the Quantity field is set to Continuous, it creates a horizontal axis along the bottom of the view. The green background and the axis help you to see that it's a continuous field.




In the example below, the Quantity field has been set to Discrete. It creates horizontal headers instead of an axis. The blue background and the horizontal headers help you to see that it's discrete.


In both examples, the Sales field is set to Continuous. It creates a vertical axis because it continuous and it's been added to the Rows shelf. If it was on the Columns shelf, it would create a horizontal axis. The green background and aggregation function (in this case, SUM) help to indicate that it's a measure.

The absence of an aggregation function in the Quantity field name help to indicate that it's a dimension.

  1. Initially when you drag any data field to the columns row it will be Discrete by default .you can change them to discrete or continuous fields.

  2. Date and numeric fields can be discrete or continuous. Based on what you select like discrete or continuous the axes and headers will change.

  3. The colors will change based on what you select like Continuous is green and Discrete is blue.

  4. Dimensions containing string or Boolean values cannot be continuous.

  5. Tableau doesn't aggregate Dimensions.

Dimensions vs LOD:

As you add dimensions the level of granularity in data changes and as you add to Rows or Columns, the number of marks in the view increases

Lets see this statement with examples:

Drag any field to the Dimensions ,Here I used category to the columns and it showing me 3marks.




Those marks just contain placeholder text, Abc, because you are only building the view's structure at this point.



Now Drag any other field and lets see marks, I used City now, Now the marks is 1198 the values in the category is multiplied by city


Now the sheet will be


Now Drag the Profit to the rows

The total is now1198 marks (three categories by cities by profit is a different number , but there are three combinations of the dimensions in the view for which there is no data in the data source).

We could continue adding dimensions to Rows and Columns and observe as the number of total marks continues to increase. Dragging a dimension to a location on the Marks card such as Color or Size will also increase the number of marks, though it will not increase the number of headings in the view. The process of adding dimensions to the view to increase the number of marks is known as setting the level of detail.

Adding a dimension to any of the columns,rows and marks changes your level of details:

The view now contains 1198 separate instances of ABCs—the view is all structure and no content. The view can now be considered complete



Measures will change the view:

When you drag a measure to the view, it is aggregated by default. The type of aggregation will vary depending on the type of view. You should always check the aggregation and change it if necessary.

When you drag a continuous field from the Data pane to Rows or Columns, Tableau creates a continuous axis for that field.


Continuous axis

If you change the profit to discrete lets see how the changes will be


Profit is changed to header


Tableau continues to aggregate values for the field, because even though the field is now discrete, it is still a measure, and Tableau aggregates measures by default.

In cases where Tableau has misclassified a field as a dimension or a measure, possibly because of the data type, you can convert it and change its role. If a measure contains numbers that don't need to be aggregated (such as a field that contains date values), you may want to convert it to be a dimension.


Thank you for Reading, Hope I share some knowledge on Dimensions and Measures.

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