Iliad Platform

Iliad Platform is an enterprise analytics application designed to centralize and leverage the Wild Code School's educational data. It provides a consolidated view of KPIs for data-driven management of the training programs. Issues addressed: - Trainers: No real-time visibility into learners' progress and satisfaction - Educational managers: Late detection of problematic quests and of students at risk of dropping out - Management: No consolidated metrics for strategic decisions Key features: - Tracking of Odyssey quest progress (progression, completion rate) - Analysis of learners' ratings and reviews on each quest - Certification pass rates by team and trainer - Trainers' weekly feedback (Notion) - Centralization of issues reported via Slack - Satisfaction metrics (NPS, surveys) Use cases: 1. Educational leads — Identify quests that need adjustments 2. Trainers — Follow feedback and continuously improve sessions 3. Management — Consolidated KPIs for strategic decisions

Star schema data model optimized for OLAP analysis, with a clear separation between dimensions and facts. Dimension tables: - dim_expedition — Information on expeditions and learning paths - dim_quests — Quest details and difficulty levels - dim_crews — Teams and organization - dim_users — Users (learners, trainers) - dim_surveys — Survey configuration - dim_missions — Missions and objectives - dim_async_cohort — Asynchronous cohorts - dim_async_courses — Asynchronous courses - dim_survey_questions — Survey questions Fact tables: - fact_adventures — Quest progress - fact_journeys — Learning paths and achievements - fact_certif — Certification results - fact_surveys_response — Survey responses and evaluations - fact_absence — Absence tracking - fact_corrections — Corrections and comments - fact_completions — Completion rates - fact_async_progressions — Asynchronous progress Hybrid storage: - DuckDB/MotherDuck — OLAP analysis, complex analytical queries - MongoDB — Unstructured data (Slack, Notion) - Redis — Cache and session management - PostgreSQL — Odyssey source (raw data)

5 heterogeneous data sources integrated through robust, orchestrated ETL pipelines. Odyssey pipeline (PostgreSQL → DuckDB): - Extraction of learner progress data - DBT transformations for the analytical model - Automatic sync to MotherDuck (cloud) - Completion metrics and pass rates Slack integration: - Automatic capture of messages and threads - Tracking of reported issues and resolutions - Bot commands (/history, /help, /stats) - Decoupled architecture with NATS JetStream Notion integration: - Two-way sync of weekly feedback - Redis cache for optimal performance - Automatic change detection HubSpot integration: - CRM sync (contacts, companies, tickets) - Import of survey responses - Export of insights to the CRM Certifications pipeline (Google Drive): - Extraction of results from Google Drive - Smart user matching - Tracking of pass rates by trainer/team

Modern full-stack architecture with frontend/backend separation and containerized infrastructure. Frontend (Angular 18+): - TypeScript 5.4+ with a modular architecture - Tailwind CSS + Angular Material for styling - Chart.js with ng2-charts for visualizations - RxJS for reactive state management - Smart search algorithm (context-aware) Backend (Python/Flask): - REST API with JWT authentication + refresh tokens - RBAC (Role-Based Access Control) - Redis cache with smart invalidation - Input validation and security Data Engineering: - DBT for transformations (dev/prod targets) - Prefect for workflow orchestration - Local DuckDB / MotherDuck cloud - Kafka/NATS for asynchronous messaging Languages used: - Python 3.8+ (backend, ETL, orchestration) - TypeScript 5.4+ (Angular frontend) - SQL (DBT models) Infrastructure: - Docker + multi-service Docker Compose - Automated GitHub Actions CI/CD - Nginx reverse proxy - Let's Encrypt SSL with auto-renewal

Production infrastructure with Prefect orchestration, automated CI/CD and built-in monitoring. Prefect orchestration: - Microservices API (port 8000) for manual triggering - Freshness checks on DBT sources - Management of deployments and flow IDs - Endpoints: /health, /run/<service> - Run monitoring and recovery on errors GitHub Actions CI/CD: - Automated pipeline: lint, tests, build, deployment - Zero-downtime deployments - Multi-environment management (dev, staging, prod) - Automatic SSL with Let's Encrypt + cron renewal Docker services: - Frontend (Nginx + static Angular) - Backend API (Flask) - MongoDB (users, Slack messages) - Redis (cache) - Prefect (orchestration) - NATS (message broker) - Certbot (SSL) Advanced features: - Context-aware smart search (dates, names, places) - JWT with automatic refresh - Cache with statistics and health monitoring - Structured logs and alerts