This project demonstrates a complete, company-level data analytics workflow, mirroring how data analysts work in real organizations. It covers everything from raw data ingestion and cleaning to business problem solving, SQL analysis, dashboarding, and executive-ready reporting.
The goal is to transform messy retail customer data into actionable business insights that support data-driven decision-making.
Python (pandas, numpy) – for data cleaning and transformation
SQL (PostgreSQL) – for analyzing business transactions and queries
Power BI – for creating interactive dashboards and KPIs
Jupyter Notebook – for data exploration and documentation
GitHub – for version control and portfolio hosting
Gamma AI – for business presentation deck