1) A tech company wants to analyze the performance of its software products based on user feedback ratings. The dataset includes product names, feedback scores, and comment summaries. How would you effectively visualize the average feedback score for each product?

2) Your organization needs to track employee performance metrics, including sales targets and actual sales. The dataset includes employee IDs, target sales, and actual sales. What DAX measure would you create to calculate the performance percentage?

3) A marketing team wants to evaluate the effectiveness of their social media campaigns. The dataset includes campaign names, impressions, clicks, and conversions. What visual would best display the conversion rate for each campaign?**

4) A retail store wants to understand the impact of discounts on sales. The dataset includes sales amounts and discount percentages. How would you visualize the relationship between discounts and sales?**

5) An airline wants to track flight cancellations and delays. The dataset includes flight numbers, cancellation status, and delay durations. What DAX measure would you create to calculate the average delay time for canceled flights

6) A subscription-based service wants to analyze churn rates. The dataset includes subscriber IDs, subscription start dates, and cancellation dates. What DAX measure would help calculate the churn rate?

7) A real estate agency wants to analyze property sales based on various features such as location, size, and price. The dataset includes property IDs, features, and sales prices. What visual would be most effective for comparing property prices across different locations?

8) An automotive company wants to visualize sales data across different models and regions. The dataset includes model names, sales figures, and regions. How would you create a report to analyze this effectively?**

9) A food delivery service wants to analyze the average delivery time based on various factors, including distance and order size. The dataset includes delivery times, distances, and order sizes. What type of visual would best display the relationship between these factors?

10) A company wants to analyze employee satisfaction ratings from various departments. The dataset includes employee IDs, department names, and satisfaction scores. What type of visual would best represent the average satisfaction score for each department?

11) A manufacturer wants to track the production output against targets for different products. The dataset includes product IDs, actual output, and target output. What DAX measure would you create to calculate the variance between actual and target outputs?

12) A retailer wants to analyze customer purchase patterns over the last year. The dataset includes customer IDs, purchase dates, and amounts. What type of visual would best help understand seasonal trends in purchasing behavior

13) A project manager wants to track the status of various tasks in a project management tool. The dataset includes task names, assigned team members, and completion status. What visual would best represent the status of tasks across team members?

14) A financial analyst wants to compare revenue and expenses for different business units. The dataset includes unit names, revenue, and expenses. What type of visual would effectively display this comparison?

15) A school wants to analyze student performance based on standardized test scores. The dataset includes student IDs, test scores, and grade levels. What DAX measure would you use to calculate the average test score by grade level?

16) A logistics company wants to analyze the average delivery times based on different routes. The dataset includes route names, delivery times, and distances. What DAX measure would you create to calculate the average delivery time per route?

17) A fashion retailer wants to understand the sales performance of different clothing categories. The dataset includes category names, sales figures, and inventory levels. What type of visual would best show the relationship between sales and inventory levels for each category?

18) A healthcare provider wants to track patient wait times across different departments. The dataset includes department names, patient IDs, and wait times. How would you visualize the average wait time by department?

19) An energy company wants to analyze the consumption patterns of electricity over the past year. The dataset includes monthly consumption data and customer segments. What type of visual would best represent this data?

20) In a customer analysis report, you need to calculate the retention rate, defined as the percentage of returning customers. What steps would you take to calculate this?