Top N filters in Tableau - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ dax_lod_result

intermediate

Calculate Top 3 Products by Sales

You have a dataset with Product Names and Sales Amounts. You want to create a Top N filter to show only the top 3 products by total sales. Which DAX expression correctly calculates the rank of each product to enable this filter?

Tableau

Rank = RANKX(ALL('Products'[Product Name]), CALCULATE(SUM('Sales'[Amount])), , DESC, DENSE)

A Rank = RANKX(ALLSELECTED('Products'[Product Name]), SUM('Sales'[Amount]), , ASC, Skip)

B Rank = RANKX(ALL('Products'[Product Name]), CALCULATE(SUM('Sales'[Amount])), , DESC, DENSE)

C Rank = RANKX(ALL('Products'), SUM('Sales'[Amount]), , DESC, Skip)

D Rank = RANKX(VALUES('Products'[Product Name]), CALCULATE(SUM('Sales'[Amount])), , DESC, DENSE)

💡 Hint

Use ALL to ignore filters and rank all products by total sales descending.

Option B uses ALL to remove filters on Product Name and ranks products by total sales in descending order with dense ranking, which is correct for Top N filtering.

❓ visualization

intermediate

Best Practice for Top N Filter Visualization

You want to create a dashboard showing the Top 5 customers by revenue. Which visualization approach best follows best practices for Top N filters in Tableau?

A Create a line chart with all customers and use color to highlight the top 5.

B Create a pie chart showing all customers and manually hide those outside the top 5.

C Use a bar chart with a parameter to select N and apply a filter using a calculated field ranking customers by revenue.

D Use a table showing all customers sorted by revenue and rely on scrolling to find top 5.

💡 Hint

Interactive parameters with calculated fields help users dynamically select Top N.

Option C uses a parameter and calculated field to dynamically filter and visualize the Top N customers, which is a best practice for usability and clarity.

❓ data_modeling

advanced

Handling Ties in Top N Filters

In a Top N filter scenario, some products have the same sales amount causing ties in ranking. Which approach ensures all tied products at the Nth position are included in the filter?

A Use RANKX with DENSE ranking and filter for rank <= N.

B Use RANKX with SKIP ranking and filter for rank < N.

C Use RANKX with DENSE ranking and filter for rank < N.

D Use RANKX with SKIP ranking and filter for rank <= N.

💡 Hint

Dense ranking assigns the same rank to ties and does not skip ranks.

Dense ranking assigns the same rank to tied values and does not skip subsequent ranks, so filtering rank <= N includes all tied products at the Nth rank.

🔧 Formula Fix

advanced

Why Does This Top N Filter Show Incorrect Results?

You wrote this DAX measure to filter Top 10 customers by sales: Top10Customers = IF(RANKX(ALL('Customers'), SUM('Sales'[Amount])) <= 10, 1, 0). But the filter shows fewer than 10 customers. What is the most likely cause?

Tableau

Top10Customers = IF(RANKX(ALL('Customers'), SUM('Sales'[Amount])) <= 10, 1, 0)

A The ALL function is missing the column reference, causing incorrect ranking.

B The IF statement returns 1 and 0 instead of TRUE and FALSE, causing filter issues.

C The measure uses SUM instead of CALCULATE, so context is lost.

D The RANKX function is missing the order argument, defaulting to ascending instead of descending.

💡 Hint

Check the order argument in RANKX to rank highest sales first.

By default, RANKX ranks in ascending order, so the lowest sales get rank 1. Without specifying DESC, the top 10 customers by sales are not correctly identified.

🧠 Conceptual

expert

Impact of Context on Top N Filters

In Tableau, when applying a Top N filter on a dimension, how does the filter context affect the results if the filter is applied before or after aggregation? Choose the correct statement.

A Applying the Top N filter before aggregation limits the data considered, potentially excluding relevant data and causing incorrect totals.

B Applying the Top N filter after aggregation filters the raw data rows, improving performance and accuracy.

C Top N filters always apply after aggregation, so filter context does not affect results.

D Applying the Top N filter before aggregation ensures all data is included in totals and subtotals.

💡 Hint

Think about whether filtering raw data or aggregated results changes totals.

Filtering before aggregation limits the data set early, which can exclude data needed for accurate totals. Filtering after aggregation preserves totals but may include unwanted data in detail.