How to Create Span Chart?

Background

A Tableau Span Chart helps to display dataset ranges between a minimum value and a maximum value. Businesses of all sizes can benefit immensely from a Span Chart that helps interpret key metrics. A Span Chart is also one of the most fundamental techniques we teach data visualization students due to it’s flexibility. A Span Chart improves data readability.

Tableau Span Chart Guide
Tableau Span Chart Guide

Steps to Create a Span Chart

Our Certified Tableau Professionals have created the below Span Chart keeping scalability and flexibility in mind. The Span Chart helps understand the range of two values by clear colored marks. The line joining the two data points provide a quick and efficient way to assess the gap between two values. Key performance indicator ranges of various industries can be efficiently measured using a Span Chart.

Tableau Span Chart

Tableau Desktop Span Chart provides a solid analytical tool for data analysts. Download the Tableau Span Chart Workbook above and instantly start exploring your data with a Span Chart. The colors in the Span Chart above can be customized as per your color theme. Any measure can be used to analyze the range between different data points over different parameters.

Why Create a Span Chart

A Span hart is one of the simplest yet a powerful analytical visual tool. Using a Span Chart businesses can understand range of different extreme data points. We can also use a Tableau Span Chart in combination with different dimensions. With such advanced data analysis techniques businesses can garner greater insights. Tableau Desktop provides an efficient way to create a Span Chart in different ways. We can adjust the aesthetics of the Span Chart by changing the color and sizes of the bars and circles as we need. A Span Chart is also dynamic and efficient with large volumes of data.


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Published by Rahul

Rahul is a data analyst and expert in visualizing business scenarios using data science. He has performed extensive research across varied business scenarios and datasets to come up with insightful results. Rahul is skilled in a number of programming languages and data analysis tools. When he is not busy refining business data, Rahul can be found somewhere in the Appalachian trails or in an ethnic restaurant in Chicago. All contents here are copyrighted and belongs to Rahul.

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