Top Tableau Scenario-Based Interview Questions Set - 15 (1- 8)

 

How would you identify customers who purchased in consecutive months?

Use a table calculation to compare purchase months for each customer.

Example:

DATEDIFF(
   'month',
   LOOKUP(MIN([Order Date]),-1),
   MIN([Order Date])
) = 1

---

2. How would you calculate the percentage of orders shipped late?

Divide late orders by total orders.

Example:

SUM(
IF [Ship Date] > [Required Date]
THEN 1
ELSE 0
END
)
/
COUNT([Order ID])

---

3. How would you identify the customer with the highest lifetime sales?

Use a FIXED LOD to calculate total sales per customer and rank them.

Example:

{ FIXED [Customer ID] : SUM([Sales]) }

Rank:

RANK(
{ FIXED [Customer ID] : SUM([Sales]) }
)
= 1

---

4. How would you calculate average monthly profit?

Aggregate profit at month level and average it.

Example:

WINDOW_AVG(SUM([Profit]))

Or:

SUM([Profit])
/
COUNTD(DATETRUNC('month',[Order Date]))

---

5. How would you identify regions where sales exceeded target?

Compare actual sales against target.

Example:

SUM([Sales]) > SUM([Target Sales])

Variance:

SUM([Sales]) - SUM([Target Sales])

---

6. How would you find customers who have not purchased in the last 6 months?

Calculate days since the last purchase.

Example:

DATEDIFF(
'month',
{ FIXED [Customer ID] : MAX([Order Date]) },
TODAY()
) > 6

---

7. How would you calculate the average gap between customer orders?

Find the difference between consecutive order dates.

Example:

DATEDIFF(
'day',
LOOKUP(MIN([Order Date]),-1),
MIN([Order Date])
)

Then apply:

WINDOW_AVG(
DATEDIFF(
'day',
LOOKUP(MIN([Order Date]),-1),
MIN([Order Date])
)
)

---

8. How would you identify the most profitable customer in each region?

Rank customers by profit within each region.

Example:

RANK(SUM([Profit])) = 1

Set Compute Using = Customer and Partition By = Region.

Top Tableau Scenario-Based Interview Questions Set - 14 (1- 12)

 

1. How would you calculate year-over-year profit growth?
   Compare current year profit with previous year profit.
   Example:

   (SUM([Profit]) - LOOKUP(SUM([Profit]),-1))
   / LOOKUP(SUM([Profit]),-1)
   

2. How would you identify customers with highest return orders?
   Count returned orders by customer and rank them.
   Example:

   COUNT([Return Flag])
   

3. How would you display only profitable regions?
   Filter regions where total profit is positive.
   Example:

   SUM([Profit]) > 0
   

4. How would you calculate average revenue per product?
   Divide total sales by distinct products.
   Example:

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

5. How would you identify orders with unusually high sales?
   Compare sales against average plus standard deviation.
   Example:

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

6. How would you create a sales forecast trend?
   Use Analytics pane and enable Forecast option.
   Example:

   SUM([Sales])
   

7. How would you calculate median sales value?
   Use MEDIAN aggregation on Sales.
   Example:

   MEDIAN([Sales])
   

8. How would you identify products sold in all regions?
   Compare distinct region count with total region count.
   Example:

   COUNTD([Region]) = 4
   

9. How would you create a customer aging analysis?
   Calculate days since last purchase.
   Example:

   DATEDIFF('day',MAX([Order Date]),TODAY())
   

10. How would you display profit variance from target?
    Subtract target profit from actual profit.
    Example:

    SUM([Profit]) - SUM([Target Profit])

11. How would you identify top-selling products by state?
    Use RANK calculation partitioned by State.
    Example:

    RANK(SUM([Sales])) = 1

12. How would you calculate cumulative customer count over time?
    Use running total on distinct customers.
    Example:

    RUNNING_SUM(COUNTD([Customer ID]))