SQL case study on pizza sales: analyzing orders, revenue, product popularity, and time trends using joins, aggregations, and window functions.

📊 End-to-end SQL data analysis project on pizza sales using PostgreSQL. 🛠️ SQL | PostgreSQL | Data Cleaning | Aggregations | CTEs | Window Functions

A SQL-based analysis of pizza sales data to uncover insights such as popular pizzas, sales trends, revenue generation, and top customers. The project includes SQL queries and analysis results to help understand and optimize pizza sales performance.

Pizza Sales Store Analysis (SQL Project)🧑🏻‍💻🍕 I worked on a comprehensive SQL project using MySQL to analyze pizza sales data. In this project, I created and connected four key tables—orders, order_details, and pizzas—to perform in-depth data analysis. The project involved writing optimized SQL queries to uncover insights such as total

This Power BI dashboard analyzes pizza sales data to uncover trends, customer preferences, and top-selling products. It includes SQL-based data verification, interactive visualizations, and insights into sales performance, peak hours, and regional trends to support data-driven decision-making. 🚀

This repository contains SQL projects focusing on data analysis and insights. Currently, it includes: 1. RSVP Movies Analysis - SQL queries to analyze movie trends, ratings, and genres. 2. Pizza Sales Analysis - SQL queries to explore sales patterns, customer behavior, and profitability in a pizza business.

These dashboards collectively provide a detailed analysis of sales performance, customer preferences, and product-level insights. They enable decision-makers to identify top-performing products, optimize offerings, and adjust strategies to boost revenue and efficiency.

I analyzed and visualized pizza sales data using SQL, Excel, and Power BI. By using Data visualization, and utilizing business intelligence tools to derive meaningful insights.

The goal of this project is to extract meaningful insights from pizza sales data, such as sales trends, popular items, or revenue patterns. MySQL was used for data querying and cleaning, while Excel was utilized for advanced data manipulation, pivot table creation, pivot chart generation, and building an interactive dashboard.

An analysis of pizza sales

This dataset includes detailed records of pizza sales, such as order dates, pizza categories, sizes, quantities, prices, and total revenue. It’s useful for exploring sales trends, analyzing customer preferences, and generating insights for business decisions in the food industry.

Open-source PHP tool for building MySQL pivot tables with no coding. Visual builder, MIT license, lightweight setup, free to use, modify, and distribute 🐙