Top Tableau Scenario-Based Interview Questions Set - 18 (1- 5)

 

How would you identify customers whose sales increased by more than 20% compared to the previous year?

Calculate YoY growth and filter customers above 20%.

Example:

(
SUM([Sales]) - LOOKUP(SUM([Sales]),-1)
)
/
LOOKUP(SUM([Sales]),-1)
> 0.20

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2. How would you calculate the average number of orders per customer?

Divide total distinct orders by total distinct customers.

Example:

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

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3. How would you identify products that have never generated profit?

Filter products whose total profit is zero or negative.

Example:

SUM([Profit]) <= 0

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4. How would you calculate the percentage of customers contributing to 80% of sales?

Use cumulative sales percentage and count qualifying customers.

Example:

RUNNING_SUM(SUM([Sales]))
/
TOTAL(SUM([Sales]))
<= 0.8

Sort customers by Sales descending before applying the calculation.

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5. How would you identify the most recent order for each customer?

Use a FIXED LOD to get the latest order date.

Example:

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

Then filter:

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

to display only the latest order record per customer.

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