Creating Data Analysis Dashboard for Food Story

Project Description: Creating Data Analysis Dashboard for Food Story

I have placed all the queries I used on the following GitHub repository.

Data Set Repository Link

Background:

Imagine you are a data analyst at Food Story, a cloud kitchen operating in Indonesia. You are tasked with creating an interactive dashboard to help the management team understand Food Story's performance better. Leveraging your skills in Google Sheets, SQL, and Power BI, you will collect and analyze data from various sources to create informative visualizations and an interactive dashboard. The final dashboard should feature clear and understandable visualizations, allowing the management team to explore data in various ways.

Task and Objectives:

Customer Dataset:

1. Show total sales by customer name.

2. Present figures detailing total orders and total users by sales type.

3. Create visual cards displaying the total number of customers and total orders.

4. Place a text box and write insights derived from all the information.

Sales Report [Branch Level]:

1. Create filters for date and branch name.

2. Display visual cards showing the total bill and grand total.

3. Show time-series figures comparing the grand total and total bill in one chart.

4. Generate figures to determine the busiest times for orders.

5. Display figures to compare the contribution of grand totals between weekdays (Mon, Tue, Wed, Thu) and weekends (Fri, Sat, Sun).

6. Show figures to identify which branches contribute more.

7. Add a text box and write insights or recommendations found from all the information.

Sales Report [Menu Level]:

1. Create filters for date, city, and visit purpose.

2. Display figures to see the quantity of the most frequently sold menus and the highest revenue from menus.

3. Use a decomposition tree to show the menu selection journey based on hierarchy: menu category -> menu category detail -> menu.

4. Present figures depicting the contribution of each menu based on revenue.

5. Utilize a scatter plot to show if there is a correlation between lower menu prices and quantity sold. Does cheaper menu pricing have a positive correlation with quantity?

6. Add a text box and write insights or recommendations found from all the information.

Sales Report [Customer Level]:

1. Create filters for date, branch name, city, and visit purpose.

2. Display visual cards showing sales orders and grand totals.

3. Present time-series figures comparing grand totals and total bills in one chart.

4. Display figures showing how many orders used promotions vs. those that did not (excluding "Open bill discount" promotions).

5. Show figures to examine which promotions contribute significantly but are not included in the no-promotion and "Open bill discount" categories.

6. Display figures to determine the busiest times for orders.

7. Present figures to compare the contribution of grand totals between weekdays (Mon, Tue, Wed, Thu) and weekends (Fri, Sat, Sun).

8. Show figures to see which branches contribute more.

9. Add a text box and write insights or recommendations found from all the information.

Conclusion:

This project will provide significant value to Food Story, aiding the management team in making better decisions and providing in-depth insights into the company's performance. I hope this dashboard will assist in planning Food Story's future and enhancing operational efficiency.