Section B — Data Visualization

6. Create a chart showing Total Sales by Product Category.

7. Create a chart showing Total Sales by City.

8. Create a monthly sales trend using the Order Date.

9. Create a chart showing the distribution of customers by Customer Type.

10. Create a chart showing the relationship between Discount Percentage and Total Price.

11. Create a chart showing the relationship between Delivery Distance and Delivery Delay.

12. Create a chart comparing Profit across different Regions.

13. Create a chart showing the relationship between Room Area and Estimated Cost.

28. Find one interesting relationship or trend in the dataset that management may not immediately notice. Visualize it using an appropriate chart.

29. Based on your analysis, provide three actionable business recommendations.

• Prioritize high-value segments and orders: Total Price is strongly associated with Gross Sales and Profit; focus sales coverage and cross-sell efforts on Corporate customers and the West region.

• Reduce Consumer churn: Consumer churn is highest at approximately 45.7%; deploy post-purchase engagement, loyalty incentives, and targeted win-back campaigns.

• Improve Standard shipping reliability: Standard shipping has the highest late-delivery rate at approximately 30.1%; strengthen SLA monitoring, carrier

Section C — Regression

Section C — Classification

Section E — Business Problem Challenge

26. Identify one additional regression problem that can be solved using this dataset. Build and evaluate the model.

27. Identify one additional classification problem that can be solved using this dataset. Build and evaluate the model.

30. Knime final workflow

Section A — Data Preparation & Expressions