Big Data Storage Capstone Project

Principle

  • Work in teams of 4 people.
  • Topic of your choice description, including story, objective, indicators, and analytics questions (indicators) – discuss with the lecturer about your idea.
  • Combine more than one dataset (see below)
  • Preferably adhere to sustainable development goals (https://www.agenda-2030.fr/en/the-17-goals/)

Methodology

Use ≥2 open-data providers (with ≥2 releases/snapshots where possible), land them in a mini data lakewith a small metadata catalogue, transform them with Talend into a relational data warehouse (star or snowflake), and publish a Tableau dashboard that runs backend OLAP queries to compute your business indicators (see details below).

Final Deliverables

  • Digital poster explaining the approach and results: before02/12/2025 at midnight
    • Division of the work within the team (separate document)
    • General idea of the project
    • Data model adopted
    • Processes created
  • Demo fest 05/12/2025 (dashboard and results obtained)

Figure 1 Partial deliverables calendar

Evaluation Criteria

  • Originality of the concept and the degree of alignment with the Sustainable Development Goals
  • Use of different data sets described in the data lake
  • An exploration interface for choosing portions of data for building a DW
  • Data preparation and LT (Loading and Transformation) process to populate DW
  • Analytics queries (OLAP)
  • Relevance and interest of the indicators produced
  • Level of difficulty (complexity of database, processes, etc.)

Material

List of tutorials

Follow this link to see an example for Talend: 

  • http://www.osaxis.fr/talend-open-studio-par-lexemple/
  • https://business-intelligence.developpez.com/tutoriels/etl-open-source/?page=Introduction
  • https://fr.talend.com/products/data-preparation

Open data collections 

[1] https://www.tableau.com/fr-fr

[2] https://www.qlik.com/us/home