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