This project demonstrates SQL techniques used by analysts to explore, clean, and analyze pizza sales and customer data. The analysis focuses on understanding order patterns, revenue, customer behavior, and menu performance to support business decision-making.

Pizza Sales Report project, where we leverage SQL for data analysis and Power BI for creating interactive visualizations. This project provides in-depth insights into pizza sales data, including daily and monthly trends, sales by pizza category and size, and identifying top-selling pizzas based on revenue, quantity, and total orders.

Backend codes for a Pizza and Cake sales business. Runs on SQL Server and ASP.NET Web API. It was developed by a test-driven approach and is very secure, scalable and maintainable.

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Pizza sales insights by using SQL.

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Analyzing Maven Pizza's sales performance and business insights by exploring key metrics, product trends, customer behavior, and peak sales periods, utilizing SQL for querying and Excel for dashboard visualizations.

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Pizza Sales Analysis using MySQL 🍕📊 | End-to-end SQL project to analyze pizza sales data: revenue, best & worst-selling pizzas, sales trends by category, size, and time. Includes SQL queries & insights for data-driven decisions.

Analysis of pizza store sales by creating a dashboard using SQL and PowerBI

Pizza Hut Sales Analysis is a SQL project that explores pizza sales data. It provides insights on total orders, revenue generation, top-selling pizzas, popular pizza sizes, and revenue distribution by pizza type and category, offering key data for business analysis and optimization.

Pizza Sales Analysis (SQL) Analyzed pizza sales data using MySQL to uncover business insights. Used CTEs, JOINs, and window functions to calculate revenue, rank pizzas by category, identify best/worst sellers, and evaluate category-wise performance. Includes PDF report with SQL queries.

The Pizza Sales SQL Project is a data analysis project that utilizes SQL to extract meaningful insights from a pizza restaurant’s sales data. The goal is to help the business make informed decisions by analyzing sales performance, customer preferences, and operational trends.

Pizza Sales Analysis project using **SQL & Excel**. Includes SQL queries for sales insights and an interactive Excel dashboard for visualization. Analyzes revenue, orders, best/worst sellers, busiest days & times, and sales by category/size.

Creating a "Capstone Project on End-to-end data analysis into "Pizza_Sales Database" by using SQL, Python & Power BI

In this project the analysis made on the pizza sales reporty by using sql. Various tasks are performed in it.

This project focuses on analyzing pizza sales data using SQL and visualizing insights with Power BI. The dashboard includes key performance metrics such as Total Revenue, Average Order Value, Total Pizzas Sold, and Order Trends. It also highlights top and bottom-performing pizzas by revenue and sales percentage by pizza category and size.

pizza_salesnow is a powerful SQL query designed to analyze pizza sales data across multiple dimensions—type, category, quantity, price, and revenue. It joins and aggregates data from pizza_types, pizzas, and order_details to deliver ranked insights into the top-performing pizzas by revenue within each category.

This repository contains a comprehensive SQL analysis of pizza sales data. The project explores various business insights by querying a relational database, including order trends, revenue breakdowns, and popular pizza choices.

This project analyzes pizza sales data using SQL. It includes various queries to extract insights such as total revenue, most popular pizza types, order distribution by time, and cumulative revenue trends.

Interactive dashboard built using Power BI to analyze pizza sales data. Includes key insights on top-selling pizzas, revenue trends, order patterns, and performance by size and category — powered by SQL for backend data processing

In this project, I worked with four key tables: orders, order_details, pizzas, and pizza_types, using SQL to: Identify the most popular pizza types and sizes. Analyze sales trends by day and time. Provide insights on average sales per order Project Highlights: 📈 Improved understanding of customer preferences. 🕒 Analysis of peak sales times for b

Analyzed pizza sales data using SQL across four tables to uncover revenue, top-selling pizzas, and order trends by size, category, and time. Gained insights on daily averages and high-performing items, enhancing SQL skills and supporting data-driven decisions.

Analyzed pizza sales data using Excel & SQL. Performed data cleaning, calculated KPIs (revenue, avg order value), and created visualizations (trends, sales by category/size, top/bottom sellers). Identified customer preferences and sales performance for data-driven decisions.

🍕 Turning slices into insights — an interactive Power BI dashboard powered by SQL and DAX to uncover what’s really cooking in pizza sales performance.

This SQL-based project analyzes Pizza Hut's sales data to uncover insights about customer behavior, product performance, and store efficiency. It focuses on optimizing decision-making by leveraging advanced SQL techniques.

Analyzed pizza sales data using SQL and Excel to uncover key business insights. Performed data cleaning, transformation, and created an interactive Excel dashboard. Identified top-selling pizzas, peak order times, and sales trends by size and category. Showcases end-to-end skills in data analysis and visualization.

This project focuses on analyzing pizza sales data using SQL Workbench to derive key business insights. The goal is to identify ordering patterns, revenue trends, and top-selling pizzas to help optimize business decisions. By utilizing structured queries and data analysis techniques, the project provides a clear understanding of sales performance.

Analyzed pizza sales data using SQL, including basic queries for total orders and revenue, as well as advanced analyses like revenue contribution by pizza type and cumulative revenue over time. Gained hands-on experience in SQL querying, data analysis, and database management to derive actionable insights from complex datasets.

This project delivers a detailed analysis of pizza sales data using SQL Workbench, organized into basic, intermediate, and advanced levels. It covers key aspects such as total orders, revenue calculation, and identifying top pizzas by size and type. Ideal for enhancing SQL skills and gaining insights into retail data analytics.