Mastering Tableau 2018.1, Second Edition 8.4: Clustering Data in Tableau

The video tutorial explains how to identify outliers using K-means clustering in Tableau. It covers creating scatter plots, applying clustering features, and editing clusters. The tutorial also describes how to analyze cluster inputs and outputs, and understand model values like P value and F statistic. The video concludes with a brief mention of the next topic, Pareto charts.

What is the purpose of using the K means cluster algorithm in data analysis?

How does the clustering process help in identifying outliers in a dataset?

Describe the steps involved in creating a scatter plot for data analysis.

What options are available for editing clusters in the analysis tool?

Explain how the model values such as P value and F statistic are used in data analysis.