SQL Analysis for orders Pizza Restaurant and Power BI Dashboard

A Java-based Grocery Store Management System with separate Admin and User apps. Built using Swing and SQL Server, it supports product, customer, and employee management with a fully interactive UI.

MS SQL Database system created for "Restaurant Management". Developed in MS SQL Server 2019 Management Studio for 3rd grade(junior year) Database Systems course.

Create and deploy an efficient data warehouse using Microsoft SQL Server tools, optimizing loading processes with SSIS for ETL workflows. Extend functionality with SSAS, SSRS, and pivot tables for in-depth analysis, enhancing insights through Power BI visualization.

🏃🏻‍♂️ Personal Fitness Management System: Helps users track fitness routines, monitor progress, and manage food-intakes. It features a user-friendly interface, calorie tracking, manage workout activities, and data analysis tools. Built with Python, MySQL, and CustomTkinter.

The task was given to assess my understanding of writing complex SQL queries as a recruitment process for data analyst position in Dcluttr.

The repository contains sample MS-SQL files from my work.

edX course Microsoft: DAT201x Querying Data with Transact-SQL

This project walks through a full customer shopping behavior analysis using real transactional data. It combines Python for data cleaning and exploration, SQL for deeper business queries, and Power BI for an interactive dashboard. The goal is to uncover purchase patterns, customer segments, revenue trends, and actionable insights from raw data.

Develop and Deploy a Datawarehouse solution. Employed MS SQL Server Management Studio to build a data warehouse and increased data loading efficiency and Implemented MS SQL Integration Services (SSIS) to devise and execute ETL processes. BI II project, Building from the Data Warehouse a SSAS, SSRS, Analysis in pivot tables and Data Visualization

to develop data pipeline using the EDA and advanced analytics/ MS SQL server, create customers.gold_reports and sales.gold_reports.

Microsoft SQL Server tools and utilities

A multi-tool data analytics project that explores and analyzes bank loan data to reveal approval trends, borrower behavior, risk patterns, and key financial insights. The analysis is done using SQL queries, Python for exploratory data analysis and visualization, Excel for preliminary investigation, and Power BI dashboards for interactive reporting.