Pareto analysis in Tableau - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ dax_lod_result

intermediate

Calculate cumulative percentage for Pareto analysis

You have a sales dataset with categories and sales amounts. Which Tableau calculated field formula correctly computes the cumulative percentage of total sales by category for a Pareto chart?

A RUNNING_SUM(TOTAL(SUM([Sales]))) / SUM([Sales])

B SUM([Sales]) / RUNNING_SUM(TOTAL([Sales]))

C RUNNING_SUM(SUM([Sales])) / TOTAL(SUM([Sales]))

D TOTAL(SUM([Sales])) / RUNNING_SUM(SUM([Sales]))

💡 Hint

Think about how to accumulate sales and then divide by total sales to get a percentage.

The correct formula uses RUNNING_SUM to accumulate sales by category in order, then divides by the total sales using TOTAL to get the cumulative percentage. This is essential for Pareto analysis to show the cumulative contribution.

❓ visualization

intermediate

Best visualization for Pareto analysis

Which visualization best represents a Pareto analysis in Tableau to show the 80/20 rule clearly?

A A bar chart sorted descending by category sales with a line chart overlay showing cumulative percentage

B A pie chart showing sales percentage by category

C A scatter plot of sales vs. category

D A stacked bar chart showing sales by category and region

💡 Hint

Pareto analysis combines individual values and their cumulative impact.

The classic Pareto chart combines bars sorted by descending value with a line showing cumulative percentage. This helps identify the vital few categories contributing most of the sales.

❓ data_modeling

advanced

Data preparation for Pareto analysis with multiple dimensions

You want to perform Pareto analysis on sales by product category and region. What is the best data modeling approach in Tableau to enable this?

A Create separate data sources for category and region and blend them in Tableau

B Use a pivoted data source with sales as columns and categories as rows

C Aggregate sales by category only and ignore region for Pareto analysis

D Use a single data source with category, region, and sales columns; then create calculated fields for cumulative sales by category and region combined

💡 Hint

Think about how to analyze combined dimensions in one dataset.

Having all relevant dimensions and measures in one data source allows Tableau to calculate cumulative sales correctly across combined categories and regions for Pareto analysis.

🔧 Formula Fix

advanced

Identify the error in Pareto cumulative calculation

A Tableau user wrote this calculated field for cumulative sales percentage: RUNNING_SUM(SUM([Sales])) / SUM([Sales]). What is the issue with this formula?

Tableau

RUNNING_SUM(SUM([Sales])) / SUM([Sales])

A RUNNING_SUM cannot be used with SUM aggregation

B It divides cumulative sales by the current row sales, not total sales, causing incorrect percentages

C The formula is correct and will produce the expected cumulative percentage

D SUM([Sales]) should be replaced with TOTAL(SUM([Sales])) to fix syntax

💡 Hint

Check what the denominator represents in the formula.

The denominator SUM([Sales]) returns the sales for the current row only, not the total sales. For cumulative percentage, the denominator must be the total sales across all rows, which requires TOTAL(SUM([Sales])).

🧠 Conceptual

expert

Understanding Pareto principle application in BI

In a Pareto analysis dashboard, you notice that 30% of categories contribute to 90% of sales. What does this imply about your data and business focus?

A A small number of categories generate most sales, so focusing on them can improve business efficiency

B Sales are evenly distributed across all categories, so no category is more important

C The data is incorrect because Pareto always shows 80/20 split

D You should ignore the top categories and focus on the remaining 70% for growth

💡 Hint

Pareto principle means a few causes create most effects.

The Pareto principle states that a small percentage of causes (categories) often account for a large percentage of effects (sales). This insight helps prioritize business efforts on the vital few.