What Are Different Data Type in Tableau?


Heather Bennett

Tableau is a powerful data visualization tool that allows users to explore and analyze data in an interactive and intuitive manner. In Tableau, data is organized into different types, each serving a specific purpose. Understanding these data types is essential for effectively working with and visualizing your data.

1. Dimensions

Dimensions are categorical or qualitative variables that provide context to the data being analyzed.

They are typically non-numeric and represent different categories or groups. Examples of dimensions include product categories, geographic locations, and customer segments.

1.1 String

String dimensions contain text values, such as names, addresses, or descriptions. They are often used for labeling and grouping data based on textual information. Tableau automatically recognizes text fields as string dimensions.

1.2 Date & Time

Date & Time dimensions store temporal information like dates or timestamps. Tableau provides various date functions and options to explore and analyze time-based trends in your data effectively.

2. Measures

Measures, also known as quantitative variables, represent numeric values that can be aggregated or compared mathematically. They are typically used for performing calculations or creating visualizations based on numerical analysis.

2.1 Continuous

Continuous measures consist of numeric values that can be measured along a continuum or scale. Examples include sales revenue, temperature readings, or distances traveled.2 Discrete

Discrete measures, also known as whole number measures, represent countable quantities or distinct categories with no intermediate values between them. Examples include the number of customers, the count of products sold, or the number of orders placed.

3. Aggregated Measures

Aggregated measures are calculated values derived from aggregating or summarizing data across dimensions. Tableau offers a range of aggregation functions to perform calculations on measures, such as sum, average, minimum, maximum, and more.

4. Bins

Bins allow you to group continuous data into discrete intervals or ranges. This is particularly useful when working with large datasets or when you want to analyze data based on specific intervals rather than individual values.

5. Sets

Sets are custom subsets of your data that you can create based on specific conditions or criteria. They allow you to focus on a specific subset of your data for analysis or visualization purposes.

6. Geographic Roles

Geographic roles enable Tableau to interpret and visualize location-based data accurately. By assigning geographic roles to dimensions, such as country, state, city, latitude, and longitude, you can create maps and geospatial visualizations with ease.


In Tableau, understanding the different data types is crucial for effectively analyzing and visualizing your data. Dimensions provide context and qualitative information while measures offer quantitative insights.

Aggregated measures allow for summarizing information across dimensions while bins and sets help in grouping and focusing on specific subsets of data. Lastly, geographic roles facilitate accurate representation of location-based information in Tableau.

The proper utilization of these different data types in Tableau will enhance your ability to explore patterns and gain valuable insights from your data.

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