Top Tableau Scenario-Based Interview Questions Set - 17 (1- 10)

 

How would you calculate the percentage of total sales for each product?

Divide product sales by total sales.

Example:

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

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2. How would you identify customers who placed only one order?

Count distinct orders per customer and filter those with exactly one order.

Example:

COUNTD([Order ID]) = 1

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3. How would you calculate the average sales per day?

Divide total sales by the number of distinct order dates.

Example:

SUM([Sales]) / COUNTD([Order Date])

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4. How would you identify the month with the highest sales?

Rank monthly sales and select Rank 1.

Example:

RANK(SUM([Sales])) = 1

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5. How would you calculate the sales variance from the previous month?

Subtract previous month's sales from current month's sales.

Example:

SUM([Sales]) - LOOKUP(SUM([Sales]),-1)

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6. How would you identify products contributing less than 1% of total sales?

Calculate contribution percentage and filter.

Example:

SUM([Sales]) / TOTAL(SUM([Sales])) < 0.01

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7. How would you calculate the average order value by region?

Divide regional sales by distinct order count.

Example:

SUM([Sales]) / COUNTD([Order ID])

Place Region in the view.

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8. How would you identify customers who generated a loss?

Filter customers whose total profit is negative.

Example:

SUM([Profit]) < 0

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9. How would you calculate the percentage of returned orders?

Divide returned orders by total orders.

Example:

COUNT(
IF [Returned] = "Yes"
THEN [Order ID]
END
)
/
COUNT([Order ID])

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10. How would you identify the best-performing state within each region?

Rank states by sales within each region.

Example:

RANK(SUM([Sales])) = 1

Compute Using: State
Partition By: Region

Top Tableau Scenario-Based Interview Questions Set - 16 (1- 5)

 

1. How would you calculate Customer Retention Rate in Tableau?

Calculate customers who purchased in both current and previous periods divided by total customers.

Example:

COUNTD([Retained Customer ID])
/
COUNTD([Customer ID])

A retained customer can be identified using a Set or LOD calculation.

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2. How would you identify the Top 3 Products within each Category?

Use Rank table calculation partitioned by Category.

Example:

RANK(SUM([Sales])) <= 3

Set Compute Using = Product and Restart Every = Category.

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3. How would you calculate a customer's first purchase date?

Use a FIXED LOD expression.

Example:

{ FIXED [Customer ID] : MIN([Order Date]) }

This returns the first purchase date regardless of filters in the view.

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4. How would you show customers whose sales are above their regional average?

Compare customer sales against the average sales within the region.

Example:

SUM([Sales])
>
WINDOW_AVG(SUM([Sales]))

Compute using Customer and partition by Region.

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5. How would you identify the Bottom 10 Products by Profit?

Use Rank on Profit in ascending order.

Example:

RANK(SUM([Profit]),'asc') <= 10

Filter TRUE to display the 10 least profitable products.