These examples show the consulting value behind my work: cleaner reporting foundations, clearer operational metrics, better forecasting workflows, and business-facing analytics outputs.
I built this as an end-to-end analytics engineering and BI workflow for the kind of problem many growing teams face: raw files exist, but the data is not ready for trusted reporting. The project moves from CSV cleaning and validation into PostgreSQL, dbt transformations, dimensional modeling, data quality checks, and dashboard-oriented SQL for operational and product analysis.
This project was built for the HAVI / NIU Quick Service Restaurant Demand Forecasting Challenge, where the business problem was predicting daily menu-item demand by restaurant. The workflow combined exploratory analysis, time-based validation, calendar, weather, promotion, and historical demand features, plus gradient boosting models designed around the competition's wMAPE objective.
This project analyzes an ecommerce A/B test by cleaning experiment data, validating the control and treatment setup, and comparing conversion behavior and session engagement across groups and countries. It demonstrates how experimentation work should connect data validation, SQL analysis, Python workflows, and business interpretation before a team acts on test results.
More examples that show the range of problems I can support: engagement analysis, business strategy, predictive modeling, dashboarding, and application workflows.
This project focused on analyzing engagement patterns and translating findings into recommendations that could support stronger outreach and program decision-making.
A collaborative case project centered on structured business analysis, recommendation development, and communicating insights clearly as a team.
A web development project that gave me hands-on experience building a more complete application workflow beyond analytics alone.
A predictive analytics project focused on identifying patterns related to employee attrition and turning modeling output into insights that could support retention decisions.
A dashboarding project built around exploratory analysis, visualization, and presenting trends in a way that is both engaging and easy to interpret.