3A Superstore Analytics — Inflation-Adjusted Revenue Analysis & Forecasting
Analyzed nominal and inflation-adjusted revenue for a Turkish supermarket chain, built BigQuery/dbt analytics models, and created Python forecasts and Power BI reporting for a team analytics project.
Project Overview
This was a 4-person analytics project using a Turkish supermarket dataset spanning from 2021 to 2023. Because this period saw high inflation, nominal revenue alone could overstate business growth. My analysis focused on separating nominal growth from inflation-adjusted real growth and extending the analysis with 2024 revenue forecasts.
For the full work, you can view the project website, read my analysis, or examine the GitHub repo.
My contribution
- Set up the shared analytics workflow across Git, BigQuery, dbt, Python, and Jupyter.
- Integrated inflation data from the TCMB EVDS API and used it to calculate real revenue metrics.
- Built dbt SQL models from staging through analytics marts used by the dashboard and forecasting notebooks.
- Developed regression-based revenue forecasts in Python with scikit-learn.
- Contributed to the Power BI dashboard, team presentation, and deployed the project website.