Nova Super-App Analytics — Marketplace Opportunities & Demand Drivers
Analyzed global marketplace performance and growth opportunities, and local demand drivers using SQL, Python, and Tableau. Built an end-to-end pipeline and enriched data via APIs for predictive modeling.
Overview
This project was a 3-person team effort working with a Kaggle dataset on Nova, a fictitious super-app providing services like e-commerce, food delivery, grocery shopping, ride hailing, and digital wallet. Nova app operated in the global markets which allowed me to analyze marketplace performance and determine which markets display high potential for business growth. I supported my analysis by enriching the data via external APIs
To check the full project visit our project website and GitHub repo.
My contribution
- Set up & configured our coding environment and dbt & BigQuery connection.
- Enriched data via REST Countries, World Bank Open Data, and Open-Meteo APIs.
- Built SQL-based dbt models from staging layer to analytics marts to be consumed by Jupyter notebooks and Tableau dashboards.
- Implemented feature engineering, regression modeling to predict the strongest demand drivers, and clustered markets with KMeans.
- Contributed the Tableau dashboard, team presentation, and the project documentation & website.