How to Create Pareto Chart?

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Background

Vilfredo Pareto is a noted Italian economist introduced the concept of Pareto efficiency and helped develop the field of microeconomics. The Pareto principle was named after Vilfredo Pareto. It was built on his observations that 80% of the wealth in Italy belonged to 20% of the population. This can be applied in many other causal scenarios as well. Let’s learn how to create a Pareto Chart using Tableau.

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Tableau Pareto Chart Guide
Tableau Pareto Chart Guide

Steps to Create a Pareto Chart

Create a Pareto Chart that contains both bars and a line graph like below. The bars are arranged in descending order of values. The line represents the cumulative total. For example as a use cause, to lower the volume of shipped late arrival by 70-80%, it is usually sufficient to solve the top three issues. Pareto charts are especially useful in quality control. Download the Tableau Pareto Chart (.twbx) Workbook below.

Tableau Pareto Chart
Tableau Pareto Chart

Tableau Desktop provides a robust way to create Pareto Charts. Our talented Tableau experts have delicately crafted the above Pareto chart that can be used in any scenario. The main purpose of a Pareto chart is to highlight the most important factors among a large set of possible factors. Addressing these top factors will essentially help making the maximum impact.

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Why Create a Pareto Chart

A Pareto Chart is a very useful tool to derive insights about the most important factors that are impacting a specific business cause. A powerful chart that can help understand key business metrics, a Pareto chart is widely used in all fields of industry today. Analysts of all domains can benefit from a Pareto Chart. Tableau Desktop provides customization options in a flexible way to create a Pareto Chart. Download the Pareto Chart above to explore the logics. The Pareto Chart helps easily identify the top factors contributing to the largest measurable impact.

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Published by Rahul Bhattacharya

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.

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