<aside> ✅

Status : Complete

</aside>

Timeline: Dataset: Nov 15, 2025 – Feb 12, 2026 (90 days)

Tools: Tableau Public, Python (pandas, scipy, seaborn, matplotlib)

Dataset: AI-generated · 90 rows · 11 variables

Dashboard: View on Tableau Public →

GitHub: https://github.com/jpicartz/Vitalquest-Wellness-Analytics

Overview


VitalQuest Performance Analytics is a full-cycle data analytics project built to demonstrate end-to-end analytical thinking — from dataset design through visualization and statistical validation. The dataset was AI-generated to simulate 90 days of individual wellness tracking across nutrition, sleep, activity, and recovery metrics.

The project was built in two layers: a Tableau Public dashboard for visual storytelling, and a Python analysis to validate the patterns observed in the charts statistically.

Dataset


The dataset contains 90 daily records across 11 variables covering the key dimensions of wellness performance.

Dataset structure

Variables: Date, Calories, Protein_g, Carbs_g, Fat_g, Micronutrient_Score, Sleep_Hours, Steps, Workout_Intensity, Energy_Level, Recovery_Score

Records: 90 rows (Nov 15 2025 → Feb 12 2026)

Source: AI-generated synthetic dataset

Format: CSV

Tableau Dashboard