Projects

Applied data engineering: from data collection to decision-making

Flagship Project
AulaMetrics
A full psychosocial assessment and educational data analytics platform for schools, built on Odoo.

The problem

Spanish schools routinely need to run standardized psychosocial assessments (well-being, risk indicators) but typically lack a system to schedule them, collect anonymous responses at scale, analyze results, and flag risk automatically — counsellors are left doing this manually with spreadsheets.

The solution

AulaMetrics is a complete module built on Odoo 17 Community Edition that lets schools schedule standardized evaluations, collect anonymous responses through unique tokens, automatically analyze results with risk detection, and generate role-differentiated dashboards and reports for administrators, counsellors, tutors and school leadership.

Tech stack

Odoo 17 (Python 3.10+)
PostgreSQL 14+
pandas
Chart.js
d3-cloud
Bootstrap 5
QWeb
HTML5 / CSS3 / JS
Docker Compose
Modular 3-layer architecture

Presentation, application and data layers with a purpose-built entity-relationship model: academic groups, evaluations, questionnaires, participations, alert thresholds, alerts and metrics.

Privacy & security by design

Four-level role system (administrator, counsellor, tutor, school leadership) with row-level access rules in Odoo, aggregated-data anonymization for tutors/leadership, GDPR/LOPDGDD-aware handling of minors' data, a session-less public portal secured with UUID v4 tokens, and HTML sanitization against XSS.

Validated with real school counsellors

Demo and feedback sessions with practicing counsellors at Spanish public schools drove a significant refactor of the scoring engine — adding multi-scale support per questionnaire (e.g. SDQ, SWLS) — plus a new case-tracking and internal messaging module.

Production-ready deployment

Containerized with Docker Compose (Odoo + PostgreSQL) on a Linux server, with a documented production plan including an Nginx reverse proxy and HTTPS.

Why this matters for data analysis

AulaMetrics is an end-to-end applied data engineering project — from the data model and collection to the analytics engine and visualization — built on a domain (psychosocial well-being in schools) directly connected to my research specialty. It reflects the same pipeline thinking I apply in quantitative research, taken all the way to production software.

Final Degree Project (Higher Technician in Multiplatform Application Development, CEEDCV). Supervised by Alfredo Oltra Orengo.