https://github.com/kishorereddypudi/pizza-sales-data-analysis
Pizza Sales Analysis project demonstrates proficiency in using SQL and Power BI to analyze and visualize data effectively.
https://github.com/kishorereddypudi/pizza-sales-data-analysis
dashboard data-visualization dataanalysis database powerbi salesanalysis sql
Last synced: about 1 year ago
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Pizza Sales Analysis project demonstrates proficiency in using SQL and Power BI to analyze and visualize data effectively.
- Host: GitHub
- URL: https://github.com/kishorereddypudi/pizza-sales-data-analysis
- Owner: kishorereddypudi
- Created: 2024-08-01T12:04:19.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-08-01T12:15:53.000Z (almost 2 years ago)
- Last Synced: 2025-02-02T15:15:31.888Z (over 1 year ago)
- Topics: dashboard, data-visualization, dataanalysis, database, powerbi, salesanalysis, sql
- Homepage:
- Size: 5.01 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
This Pizza Sales Analysis project demonstrates proficiency in using SQL and Power BI to analyze and visualize data effectively, to uncover actionable insights into sales trends and product performance for a pizza restaurant.
-> PROBLEM STATEMENT
A popular pizza store wants to optimize its sales and marketing strategies to increase revenue and customer satisfaction.To achieve this, the company needs to analyze its sales data to uncover insights into customer preferences, sales trends, and product performance.The goal is to uncover insights from the data and develop actionable recommendations to drive business growth. The Client divided the problem statement into two sections;
1. KPI’s requirement
We need to analyze the key indicators for our Pizza sales data to gain insights into our business performance, we want to calculate the following metrics :
• Total Revenue
• Total Orders
• Average Order Value
• Total Pizzas Sold
• Average Pizzas Per Order
2. Charts requirement We would like to visualize various aspects of our Pizza sales data to gain insights and understand key trends. We have identified the following requirements for creating charts :
• Daily trend for Total Orders
• Monthly trend for Total Orders
• Percentage of sales by pizza Category
• Percentage of sales by pizza Size
• Total pizzas sold by pizza Category
• Top 5 best selling & Bottom 5 worst selling pizzas.
OBJECTIVE :
Conduct a comprehensive sales performance analysis for a pizza store using SQL queries and visualize the findings using Power BI. The objective is to gain insights into sales trends, revenue distribution, and top performing products to inform strategic decision-making and optimize sales strategies.
SOFTWARES USED : POWER BI 2024, MS SQL 2019
BUILDING DASHBOARD
Developed two dynamic dashboards in Power BI to cater to distinct business needs:
• The first dashboard features essential Key Performance Indicators (KPIs), including Total Revenue, Total Orders, Average Order Value, and Total pizzas sold, alongside insightful charts displaying busiest days and times, as well as sales performance trends over specific time periods. This dashboard empowers stakeholders with actionable insights to optimize operational efficiency and strategic decision-making.
• The second dashboard highlights best and worst-selling pizzas through visually engaging charts and tables, providing a comprehensive overview of pizza sales performance. By leveraging intuitive visuals and comparative analysis, this dashboard facilitates informed product management strategies and enables targeted marketing efforts to drive sales growth.
INSIGHTS :
• FRIDAYS, THURSDAYS and SATURDAYS have the highest sales volume, comprising about 47% of total weekly sales, while Sundays and Tuesdays are typically slower days with lower sales.
• The busiest hours for pizza orders are between 12:00 PM to 1:00 PM and 5:00 PM to 6:00 PM, indicating high demand during lunch time and evening time.
• Peak sales occur during the SECOND QUARTER of the year and JULY being the month with highest sale.
• LARGE-sized pizzas are the most popular choice among customers, representing about 46% of total sales, followed by MEDIUM (30%) and SMALL (22%) sizes.
• Percentage share of total sales by all four Pizza Categories are almost same with CLASSIC category being the highest followed by SUPREME category.
• Among pizzas, THAI CHICKEN PIZZA contributes to maximum sales while CLASSIC DELUXE PIZZA are the most ordered one among the customers and BRIE CARRE PIZZA holds the position of least favoured pizza.