1. Big Data Challenges [PDF]
    • Volume: Huge data collections
    • Velocity: Continuous on-line data streams
    • Variety: Big data models
  2. Applications and tools
    • Data replication and sharding [pdf]
      • NoSql Systems: experience with CouchDB [pdf] CouchWrapup [pdf]
    • Life cycle I: sanitizing experience with Pig [pdf]
    • Life cycle II: data gathering techniques: Web scrapping, data services, crowdsourcing [pdf]
      • Open data / data journalism [see examples in the project definition]
  3. Big Data Processing Platforms
    • Parallel processing for analytics : Hadoop platforms  [pdf]
    • Some elements of data analytics [pdf]
    • Big Data Management Systems [see slides section 1 & the references section]
  4. Big and smart data applications: examples
    • Elections [pdf]
    • Other applications [pdf]