Intermediate Level

1. Case: Sales Performance Analysis

Question: You're tasked with analyzing sales performance for a retail company. How would you
approach this analysis using Power BI?
- Import sales data into Power BI Desktop.
- Create visualizations such as sales trend over time, regional sales distribution, top-selling
products, and customer segmentation.
- Use measures to calculate key performance indicators (KPIs) like sales revenue, profit margins,
and customer acquisition cost.
- Implement drill-through functionality to analyze sales performance at a granular level.
- Share insights with stakeholders using interactive dashboards and reports.

2. Case: Marketing Campaign Analysis

Question: A marketing team wants to evaluate the effectiveness of their recent campaigns. How
would you use Power BI to analyze and visualize campaign performance?
- Import marketing campaign data into Power BI Desktop, including metrics such as impressions,
clicks, conversions, and costs.
- Create visualizations to analyze campaign performance metrics over time, by channel, and by
- Calculate key performance indicators (KPIs) such as click-through rate (CTR), conversion rate,
return on investment (ROI), and customer acquisition cost (CAC).
- Implement segmentation analysis to identify the most responsive audience segments.
- Share insights with the marketing team through interactive dashboards and reports

3. Case: Supply Chain Optimization

Question: A manufacturing company wants to optimize its supply chain operations. How would
you use Power BI to analyze and improve supply chain performance?
- Import supply chain data into Power BI Desktop, including inventory levels, production
schedules, lead times, and supplier performance.
- Create visualizations to track inventory levels, production throughput, order fulfillment rates,
and supplier lead times.
- Use forecasting techniques to predict future demand and optimize inventory levels accordingly.
- Implement root cause analysis to identify bottlenecks and inefficiencies in the supply chain.
- Share actionable insights with supply chain managers through interactive dashboards and

4. Case: Customer Churn Analysis

Question: A telecommunications company wants to reduce customer churn rates. How would you
use Power BI to analyze customer behavior and identify churn predictors?
- Import customer data into Power BI Desktop, including demographic information, usage
patterns, subscription details, and churn status.
- Create visualizations to analyze customer churn trends over time, by customer segment, and by
service plan.
- Calculate churn metrics such as churn rate, customer lifetime value (CLV), and churn predictors
using machine learning algorithms.
- Implement cohort analysis to understand the behavior of different customer cohorts over time.
- Share actionable insights with the marketing and customer service teams through interactive
dashboards and reports.

5. Case: Financial Performance Analysis

Question: A finance department wants to analyze the financial performance of the company.
How would you use Power BI to create financial reports and forecasts?
- Import financial data into Power BI Desktop, including income statements, balance sheets, cash
flow statements, and key financial ratios.
- Create visualizations to analyze financial performance metrics such as revenue growth, profit
margins, liquidity ratios, and return on investment (ROI).
- Use forecasting techniques to predict future financial performance and identify potential risks
and opportunities.
- Implement variance analysis to compare actual financial results with budgeted or forecasted
- Share financial insights with stakeholders through interactive dashboards and reports.

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