Transforms raw sales and dimension data into two key analytics views—customer_report and product_report—within the gold schema using T-SQL. Includes customer segmentation, product ranking, sales trends (YoY, moving averages), and revenue contribution analysis.

This project presents a fictional case study analyzing the operations of a textile company, FabricFlow, using SQL. The dataset includes information about products, sales, inventory, suppliers, and purchases. The goal is to derive actionable insights to improve operational efficiency, inventory management, and supplier performance.

This project showcases the use of SQL to analyze retail sales data for insights on customer behavior, product performance, and sales trends. It involves table creation, data cleaning, exploration, and answering real-world business questions using SQL.

First practice post-LaunchCode graduation to review the various SQL skills we learned throughout the course.

Exploration of Covid 19 official dataset using SQL queries. Data cleaning of Nashville housing dataset for effective modelling and analysis.

This repository contains more python and sql exercises, done during the bootcamp on Data Analytics at Adalab.

Analysis of Total coronavirus cases, deaths and vaccination data of countries around the world using Microsoft SQL server. Data taken from the website: ourworldindata

SQL Data Cleaning and EDA on World Layoffs Dataset using MySQL

SQL queries developed as part of a data analysis project. Includes analysis of job data, queries for insights into job categories, salaries, and customer behavior. Techniques used include JOINS, CTEs, subqueries, and aggregate functions. Inspired by DataNerd's YouTube tutorial: https://www.youtube.com/watch?v=7mz73uXD9DA

A diverse collection of SQL-based projects that solve practical business problems using relational data. From global economics to urban transport and marketing analytics, these projects highlight strong proficiency in data querying, joins, CTEs, and window functions.

This project focuses on executing advanced SQL queries on an airline database to derive meaningful insights. The queries analyze key aspects of airline operations, such as ticket bookings, passenger records, flight schedules, and aircraft details. It leverages essential SQL techniques, including joins, CTEs, aggregations and a lot more.