Retail Sales Data Pipeline & BI System

Project Overview

Designed a structured data pipeline to analyze retail sales performance across outlet types, item categories, and establishment years.

Data Engineering Approach

1. Cleaned and transformed raw retail datasets using SQL
2. Handled missing values and optimized data consistency
3. Designed relational data model for structured analysis
4. Built aggregation logic for KPIs such as total sales, average sales, and ratings
5. Prepared transformed dataset for BI layer consumption

Tech Stack

SQL | Power BI | Data Modeling | Data Cleaning | Excel

Architecture Flow

Raw Dataset → SQL Cleaning & Transformation → Structured Data Model → BI Dashboard → Business Insights

Key Insights

1. Identified top-performing outlet categories
2. Analyzed sales trends by establishment year
3. Built a structured reporting framework for decision support

GitHub Repository

(https://github.com/raselahmed2022/End-to-end-SQL-based-data-transformation-and-analytical-retail-performance-analysis)