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https://github.com/manishkr1754/food_delivery_dashboard_powerbi

Food Delivery Company Sales Analytics using PowerBI
https://github.com/manishkr1754/food_delivery_dashboard_powerbi

analytics business-intelligence dashboard data-visualization dax meal-delivery-service pareto pareto-principle powerbi powerbi-report

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Food Delivery Company Sales Analytics using PowerBI

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README 

        
# Food_Delivery_Dashboard_PowerBI

Food Delivery Company Sales Analytics using PowerBI



# Problem Statement

Your task is to create a **Power BI report** for a meal delivery company that operates in multiple cities. The report should help the fulfilment centres with demand forecasting for the upcoming weeks. The report should be based on three datasets: historical demand data for each product-center combination, product features such as category, sub-category, price, and discount, and information about the fulfilment centres such as location and city.



The report should answer the following questions posed by the sales director:



    1. Total number of orders with a date filter

    2. Revenue earned by the company

    3. Total discounted value and overall discount %

    4. Whether the business follows the Pareto principle

    5. Top 5 selling categories

    6. Influence of operational area on number of orders

    7. Effectiveness of email and product features as a mode of promotion

    8. Forecasted weekly quantity sold for each centre, city, and meal category for the next 5 weeks.



The report should be granular enough to include product information and center-meal combinations. The report should be visually appealing and interactive to allow the sales director to easily understand the level of demand for each centre and make informed decisions.



# Approach

Crafted interactive dashboard on **450k+ rows** dataset across **15 fields** using Power Query and DAX



# Outcome

Outcome Answered business related question like Total Sales, Total Orders, **Forecasting**, **Pareto Analysis** etc.



# Main Dashboard

![image](https://user-images.githubusercontent.com/114581035/213843277-0c1e3dd1-1d40-4816-a973-b65d000939a3.png)



# 1. Detailed Overview : Orders

![image](https://user-images.githubusercontent.com/114581035/213843305-4f13141a-ddee-47e8-ae0a-6bd846e84ceb.png)



# 2. Detailed Overview : Revenue

![image](https://user-images.githubusercontent.com/114581035/213843332-853a4b6c-2d28-42d4-babb-beb8dd0e1593.png)



# 3. Detailed Overview : Discount

![image](https://user-images.githubusercontent.com/114581035/213843358-2946cdd9-8f4b-40d0-9448-43ec5b33073c.png)



# 4. Detailed Overview : Pareto Analysis (Revenue-Centres)

![image](https://user-images.githubusercontent.com/114581035/213843383-1c4daffe-7b32-41a8-9859-baffd9a12308.png)



# 5. Detailed Overview : Top 5 Selling Category

![image](https://user-images.githubusercontent.com/114581035/213843404-c41b67c5-b9bc-45fc-9cb7-e95eb9d6d23b.png)



# 6. Detailed Overview : Influence of Operation Area on Orders

![image](https://user-images.githubusercontent.com/114581035/213843434-0ad02dac-8389-4485-8d18-f5301f2b7c18.png)



# 7. Detailed Overview : Email & Homepage-Effective in Promotion

![image](https://user-images.githubusercontent.com/114581035/213843450-d070dfec-f9b3-44ea-99a5-97308f6ad822.png)



# 8. Detailed Overview : Next 5 Week Forecast

![image](https://user-images.githubusercontent.com/114581035/213843463-ed486df2-6de7-4774-a52b-49d76bfe0c38.png)