Maven Northwind Traders Challenges

Executive Summary

This report analyzes data from a company that sells products to customers all over the world. The report found that:

• The company has 89 customers and 9 staff members.
• The staff is split between the USA (5 staff members) and the UK (4 staff members). The UK staff members also serve customers in Europe.
• Customers paid $917,000 for products, but $820,000 were refunded. This means that the company only made $97,000 in net income.
• United Package shipping made the most money from shipping products.
• Almost all products were refunded to customers. Meat and poultry had the least return, while confections had the most.
• Customers like Horst Kloss, Roland Mendel, Jose Pavarotti, and Paula Wilson returned the most products.
• The USA had the most product returns, followed by Germany and Austria.
• Argentina, Norway, and Poland had the least number of customers.
• There was a small irregularity in the data. Confections and produce had a refund bigger than what was ordered.

Recommendations

Based on the findings of this report, the following recommendations are made:

• The company should survey customers to find out why so many products are being returned.
• The company should focus on improving the quality of products like condiments, dairy products, seafood, and confections.
• The company should target marketing efforts to countries with a high number of customers, such as the USA, Germany, and Austria.
• The company should investigate the irregularity in the data and take steps to correct it.

Conclusion

This report has provided valuable insights into the company's sales and customer data. The recommendations in this report will help the company improve its sales and customer satisfaction.

Behind the Scenes

This report was generated using Power BI. Power BI is a business intelligence tool that can be used to analyze data and create reports. The report was created by using the following steps:

1. The data was imported into Power BI.
2. The data from seven tables were merge in Power Query of Power BI.
3. The data was cleaned and transformed.
4. The data was analyzed using Power BI's built-in tools.
5. The report was created using Power BI's reporting tools.

The report was created using custom formatting to create different amount columns and a Refunded column.

for more visit: https://github.com/Star-cj/Northwind_Trader