File and project organization in Figma - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Why organize BI project files into folders?

Imagine you have many reports, dashboards, and data sources in one BI project. Why is it important to organize these files into folders?

A To find files quickly and avoid confusion when working with many items.

B Because folders make the project run faster when loading data.

C To reduce the file size of the project automatically.

D Because BI tools require folders to save any file.

💡 Hint

Think about how you find your documents on your computer.

Organizing files into folders helps users find and manage files easily, especially in large projects. It does not affect file size or tool requirements.

🎯 Scenario

intermediate

Best practice for naming BI report files

You have multiple reports for sales, finance, and marketing. Which naming style helps your team understand the file purpose quickly?

A Final, Draft, Old

B Report1, Report2, Report3

C 2024Q1, 2024Q2, 2024Q3

D Sales_Report_2024_Q1, Finance_Report_2024_Q1, Marketing_Report_2024_Q1

💡 Hint

Think about what information helps identify the report at a glance.

Clear and descriptive file names with category and date help team members find and understand files quickly.

❓ dax_lod_result

advanced

Calculate total sales ignoring filters on Region

Given a Sales table with columns Region and SalesAmount, which DAX measure calculates total sales ignoring any filters on Region?

Figma

Measure = CALCULATE(SUM(Sales[SalesAmount]), ALL(Sales[Region]))

A SUM(Sales[SalesAmount])

B CALCULATE(SUM(Sales[SalesAmount]), ALL(Sales[Region]))

C SUMX(VALUES(Sales[Region]), Sales[SalesAmount])

D CALCULATE(SUM(Sales[SalesAmount]), FILTER(Sales, Sales[Region] = "East"))

💡 Hint

Think about how to remove filters on a specific column.

ALL(Sales[Region]) removes filters on Region, so the measure sums all sales regardless of Region filters.

❓ visualization

advanced

Choose the best visualization for comparing sales trends by product category

You want to show how sales change over time for different product categories. Which visualization is best?

A Line chart with time on X-axis and sales on Y-axis, lines colored by product category.

B Pie chart showing total sales per product category.

C Stacked bar chart showing sales per product category for a single month.

D Scatter plot with sales on X-axis and product category on Y-axis.

💡 Hint

Think about how to show changes over time for multiple groups.

Line charts are best for showing trends over time. Coloring lines by category allows easy comparison.

🔧 Formula Fix

expert

Identify the error in this DAX measure for average sales per customer

Given a Sales table with CustomerID and SalesAmount, what error does this measure cause?

AvgSalesPerCustomer = AVERAGE(Sales[SalesAmount]) / DISTINCTCOUNT(Sales[CustomerID])

Figma

AvgSalesPerCustomer = AVERAGE(Sales[SalesAmount]) / DISTINCTCOUNT(Sales[CustomerID])

A It causes a syntax error because DISTINCTCOUNT cannot be used in division.

B It returns the correct average sales per customer.

C It returns an incorrect average because it divides average sales by distinct customers instead of total sales by customers.

D It causes a runtime error due to division by zero.

💡 Hint

Think about what the formula calculates step by step.

The formula divides average sales by distinct customers, which is not the average sales per customer. The correct approach is total sales divided by distinct customers.