Variant matrix organization in Figma - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding Variant Matrix Purpose

What is the main purpose of organizing a variant matrix in a BI dashboard design?

A To display all possible combinations of product features clearly for analysis

B To reduce the number of data points by hiding variant details

C To limit user interaction by fixing variant choices

D To create a random assortment of product options without structure

💡 Hint

Think about how variant matrices help users understand product options.

A variant matrix organizes all possible combinations of product features so users can easily analyze and compare them.

❓ data_modeling

intermediate

Structuring Data for Variant Matrix

Which data structure best supports creating a variant matrix for multiple product attributes in a BI tool?

A A JSON string stored in one cell per product

B A single column listing all product names without attributes

C A flat table with columns for each attribute and rows for each variant combination

D Multiple unrelated tables without keys linking attributes

💡 Hint

Consider how BI tools use tables to filter and slice data.

A flat table with columns for each attribute and rows for each variant combination allows easy filtering and visualization in BI tools.

❓ dax_lod_result

advanced

DAX Measure for Variant Count

Given a product variant table with columns: ProductID, Color, Size, and Stock, which DAX measure correctly counts unique variant combinations available in stock?

Figma

Measure = CALCULATE(DISTINCTCOUNT('Variants'[ProductID]), FILTER('Variants', 'Variants'[Stock] > 0))

A Measure = CALCULATE(DISTINCTCOUNT('Variants'[ProductID]), FILTER('Variants', 'Variants'[Stock] > 0))

B Measure = COUNTROWS(FILTER('Variants', 'Variants'[Stock] > 0))

C Measure = DISTINCTCOUNT('Variants'[Color] & 'Variants'[Size])

D Measure = SUM('Variants'[Stock])

💡 Hint

Focus on counting unique product IDs where stock is positive.

Option A counts distinct ProductIDs filtered by stock > 0, correctly counting unique variants available.

❓ visualization

advanced

Best Visualization for Variant Matrix

Which visualization type best represents a variant matrix showing multiple product attributes and their availability?

A Scatter plot of product price vs. size

B Pie chart showing total stock per product

C Line chart showing stock trends over time

D Matrix visual with attributes as rows and columns, showing availability as values

💡 Hint

Think about how to display multiple attributes and their combinations clearly.

A matrix visual allows displaying multiple attributes as rows and columns, making it ideal for variant matrices.

🔧 Formula Fix

expert

Debugging Variant Matrix Filtering Issue

A variant matrix in a BI report shows all variants, including those with zero stock, despite a filter applied to show only available variants. Which DAX measure fix will correctly apply the stock filter?

Figma

Current measure: VariantCount = DISTINCTCOUNT('Variants'[VariantID])

A VariantCount = DISTINCTCOUNT(FILTER('Variants', 'Variants'[Stock] > 0)[VariantID])

B VariantCount = CALCULATE(DISTINCTCOUNT('Variants'[VariantID]), 'Variants'[Stock] > 0)

C VariantCount = COUNTROWS(FILTER('Variants', 'Variants'[Stock] > 0))

D VariantCount = SUMX('Variants', IF('Variants'[Stock] > 0, 1, 0))

💡 Hint

Use CALCULATE with a filter condition inside to apply context correctly.

Option B uses CALCULATE with a filter condition, correctly applying the stock filter to count only available variants.