Tableau Practice Problems with Solutions – As a Data analyst you come across many different problems to find solutions. Or as new learner data analytics tools like Tableau you would come across a problem where you stuck upon. But don’t worry, in this short blog we have come up with a Tableau Practice Problems with Solutions for you. You can take inspiration and reverse engineer this solution to your actual problem. This short blog will help you save time and drive result fast so let’s get into one of the Tableau Practice Problems with Solutions
Tableau Practice Problems with Solutions
Problem: Sales Analysis by Month and Region Dataset: A sales dataset with columns like month, region, sales amount, and quantity sold.
Objective: Analyze sales performance by month and region and identify the top-selling regions.
Solution:
- Connect Tableau to the sales dataset.
- Drag the “Month” field to the Columns shelf and the “Sales Amount” field to the Rows shelf.
- Drag the “Region” field to the Color shelf to differentiate the regions.
- Change the chart type to a line chart to visualize the sales trend over months.
- Add a filter or parameter to focus on a specific time period or region.
- Sort the regions based on sales amount to identify the top-selling regions.
Month | Region | Sales Amount | Quantity Sold |
Jan-21 | North | $10,000 | 100 |
Jan-21 | South | $8,000 | 80 |
Feb-21 | North | $12,000 | 120 |
Feb-21 | South | $9,500 | 95 |
Mar-21 | North | $9,500 | 95 |
Mar-21 | South | $11,000 | 110 |
… | … | … | … |
By following the steps mentioned above and using the provided dummy dataset, you can analyze the sales performance by month and region and identify the top-selling regions in Tableau.
Superstore dataset analysis Tableau
Here is one more example to enhance your data analytical skill Superstore dataset analysis Tableau
Problem: Profit Analysis by Product Category and Region
Dataset: Superstore dataset with columns like Order ID, Order Date, Region, Product Category, Sales, Profit.
Objective: Analyze the profit by product category and region to identify the most profitable categories and regions.
Order ID | Order Date | Region | Product Category | Sales | Profit |
---|---|---|---|---|---|
1 | 2023-01-01 | North | Electronics | $1,000 | $200 |
2 | 2023-01-05 | South | Furniture | $2,500 | $400 |
3 | 2023-02-03 | East | Office Supplies | $800 | $100 |
4 | 2023-02-10 | West | Electronics | $1,200 | $300 |
5 | 2023-03-15 | North | Furniture | $3,000 | $500 |
6 | 2023-03-20 | South | Electronics | $1,500 | $250 |
Solution:
- Connect Tableau to the Superstore dataset.
- Drag the “Product Category” field to the Columns shelf and the “Profit” field to the Rows shelf. Drag the “Region” field to the Color shelf to differentiate the regions.
- Change the chart type to a stacked bar chart to compare the profit contributions of each product category within each region.
- Add filters or parameters to focus on specific time periods, product categories, or regions. Sort the bars based on profit to identify the most profitable categories and regions.
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Tableau Practice Problems with Solutions, Tableau practice questions on Sample Superstore, Superstore dataset analysis Tableau