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📊 BDA - Big Data Analytics Project & Labs

Rendu Rémi Locquette - ESIEE 2025-2026

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🎯 Overview

This site contains the complete documentation, laboratories, and final project for the Big Data Analytics course using Apache Spark.

📚 Content

Laboratory Sessions (Laboratory_BDA/)

• Lab 0: Introduction to Spark and PySpark basics
• Lab 1: Data ingestion and transformation
• Lab 2: Advanced transformations and joins
• Lab 3: Optimization and performance tuning
• Lab 4: Advanced analytics and ML pipeline

Each lab includes:

• Practice assignments (.ipynb)
• Graded assignments with reports
• Environment setup guides (ENV.md)
• Metrics and results

Final Project (Projet_BDA/)

Bitcoin Price Direction Prediction with Blockchain Data

• End-to-end PySpark pipeline
• Blockchain data acquisition and parsing
• Feature engineering from on-chain metrics
• Machine learning model comparison
• Comprehensive analysis and reporting

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📁 Structure

rendu_remi_locquette/
├── Laboratory_BDA/
│   ├── Lab_0/ - Introduction
│   ├── Lab_1/ - Data Ingestion
│   ├── Lab_2/ - Transformations
│   ├── Lab_3/ - Optimization
│   └── Lab_4/ - Advanced Analytics
│
└── Projet_BDA/
    ├── Project.ipynb - Full pipeline
    ├── Report.md - Final report
    ├── Utils/ - Data acquisition scripts
    └── outputs/ - Results & artifacts

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🔧 Quick Links

• Resources & Downloads - All notebooks and datasets
• Support Docs - Environment setup and helpers

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✅ Requirements

• Python 3.10+
• Apache Spark 3.5+
• PySpark
• Jupyter Notebook

See individual ENV.md files for detailed setup instructions.

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Last Updated: December 2025