Clustering in Tableau - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is clustering in data science?

Clustering is a way to group data points that are similar to each other. It helps find patterns or groups without knowing the groups beforehand.

beginner

Name one common clustering algorithm used in Tableau.

K-means is a common clustering algorithm in Tableau. It divides data into groups by finding centers called centroids.

beginner

How does Tableau help visualize clusters?

Tableau colors or labels clusters on charts so you can see groups clearly. It also lets you explore cluster details interactively.

intermediate

Why is clustering called an unsupervised learning method?

Because clustering finds groups without using labeled answers. It learns patterns from data alone.

intermediate

What is a centroid in K-means clustering?

A centroid is the center point of a cluster. K-means moves centroids to best fit the data groups.

What does clustering do in Tableau?

A Groups similar data points together

B Predicts future values

C Sorts data alphabetically

D Removes duplicate data

Clustering groups data points that are similar to each other.

Which algorithm is commonly used for clustering in Tableau?

A Naive Bayes

B Linear Regression

C Decision Tree

D K-means

K-means is a popular clustering algorithm used in Tableau.

Clustering is an example of which type of learning?

A Supervised learning

B Unsupervised learning

C Reinforcement learning

D Deep learning

Clustering is unsupervised because it finds groups without labeled data.

In K-means, what is a centroid?

A The center of a cluster

B A data point farthest from others

C A type of outlier

D A label for data

A centroid is the center point of a cluster in K-means.

How does Tableau show clusters visually?

A By hiding data points

B By sorting data alphabetically

C By coloring or labeling groups

D By removing duplicates

Tableau colors or labels clusters to help users see groups clearly.

Explain what clustering is and why it is useful in data analysis.

Think about how you might sort your photos into albums without knowing the categories first.

Describe how Tableau helps you create and understand clusters in your data.

Imagine Tableau as a smart assistant that colors your data points to show groups.