Tableau-Desktop-Found Exploring and Analyzing Data Practice Question
You are analyzing customer spending behavior and notice that the 'Profit' measure is skewed by a few extreme outliers. Which technique should you use to minimize the impact of these outliers while keeping the data in the view?
⚠ Common exam trap
Candidates often incorrectly choose to filter out or delete extreme outliers, losing valuable data points instead of adjusting the visual scale.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Apply a logarithmic scale to the axis.
When outliers distort the scale of a visualization, a log scale is often the best remedy. It compresses the range of the data, allowing both the extreme high-value outliers and the smaller, more typical data points to be visible on the same chart. This preserves the entire dataset while providing a more balanced view that highlights trends across the full spectrum of values without hiding or deleting records.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Filter out the top 5% of records.
Why it's wrong here
Filtering out data is dangerous because it removes information from the analysis entirely. You lose the context of who those outliers are and why they might be occurring. It is better to use a visualization technique like a log scale to show all data rather than deleting it.
- ✓
Apply a logarithmic scale to the axis.
Why this is correct
Logarithmic scales are specifically designed for data with a large range or outliers. They compress the higher values, making it possible to see patterns in the smaller, more common values while still including the outliers in the visualization, providing a much clearer and more comprehensive view of the dataset.
- ✗
Change the aggregation from SUM to AVG.
Why it's wrong here
Changing the aggregation does not solve the issue of outliers affecting the scale. An average is still susceptible to being pulled by extreme values. A log scale is a visual transformation, whereas changing the aggregation is a mathematical transformation that doesn't necessarily address the visual distortion caused by outliers.
- ✗
Replace the measure with a calculated field.
Why it's wrong here
Replacing the measure with a calculation is unnecessary if the data itself is valid. Outliers are often the most interesting part of the analysis. A log scale allows you to see them without needing to modify the underlying data via calculations, which preserves the integrity of the original source.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Tableau (Salesforce) exam blueprint
This Tableau-Desktop-Found practice question is part of Courseiva's free Tableau (Salesforce) certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Tableau-Desktop-Found exam.