Microsoft Contoso BI Demo Dataset for Retail Industry
Create dashboard and analyze sales situation of Contoso in 2009.
- Drew a logic tree to expose the situation and not lose the dimensions to analyze.
- Used SQL to collect, gather, and clean data.
- Drew a data model of the Contoso Dataset based on a star schema.
- Collected tables and drew a new model for Contoso's sales dataset for a BI tool, based on the data model of the Contoso dataset.
- Created a metrics dictionary. Visualized the data with Power BI.
- In 2009, the number of products sold increased by 20.4% compared to 2008, the cost decreased by 8.39%, but the revenue still decreased by 9.05%. What is the cause of this problem?
- The total transactions decreased by 15.85%.
- The decrease in the average price of each product also affected Contoso's revenue in 2009.
- The number of products sold increased due to new customers and some new products, and the new customers were buying products in categories that were lower priced on average.
- The volume was up and the average selling price was reduced, which caused the mix impact to decrease and the total revenue of the company to go down.
- Create marketing campaigns to call back lost customers.
- New products may not be selling as well as expected, so it may take time and appropriate discount campaigns for consumers to accept them. A product development strategy may also be needed.
- Balance the price for each product category, each country, and each channel.