Fitness Analytics Platform

Overview

This seeded case study models a backend analytics layer for a fitness product. It turns workout completions, goal updates, and membership events into coach-facing metrics and product health reports.

Role

Nguyen's representative role is software engineer responsible for event modeling, reporting queries, scheduled aggregation, and API endpoints used by internal dashboards.

Problem

Coaches and product teams needed fast insight into engagement trends without running expensive queries against transactional tables. Activity events also arrived at different points in the user journey, which made reporting consistency difficult.

Solution

The design separates transactional writes from analytics aggregation. EventBridge routes activity events into serverless workers, PostgreSQL stores normalized reporting tables, and Redis caches high-traffic dashboard summaries for repeated coach views.

Outcome

The seeded platform demonstrates how product analytics can stay close to backend architecture while keeping operational data, reporting data, and dashboard read models clearly separated.