Big data x business

Syllabus

A French version of the method is available -> here <- .

This content is designed by Clement Levallois, Associate Professor and Chaired Segeco professor in data valuation at emlyon business school. .

These modules provide to managers an understanding of technical concepts which are now at the center of the business world: APIs, data visualization, machine learning, network analysis, text mining, big data, data protection, etc.

Each of these topics is covered more in depth in different courses at emlyon business school: see full list here.

9 modules covering important topics in big data

Each module consists in lecture materials, a bibliography and a quiz. Some modules come with an accompanying video. Check the table of content below!

Group projects

A group project can be added to these lessons. It consists in creating a collective podcast. Each group of participants must identify an expert to interview and will record an episode.

-> Check the podcasts recorded by emlyon participants in 2017/2018.

Table of content

• Module 1. What is "data", "big data" and how is it relevant to business?
  • Essential readings
  • The definition of data ( web page, slides, pdf, source)
  • The definition of big data ( web page, slides, pdf, source)
  • The definition of the "cloud" ( video, web page, slides, pdf, source)
• Module 2. Data integration and APIs
  • Essential readings
  • The headache of data integration ( web page, slides, pdf, source)
  • APIs and their business relevance ( web page, slides, pdf, source)
  • Slideshare by John Musser on 20 business models for APIs.
• Module 3. CRMs and segmentation / clustering
  • Essential readings (same as previous week)
  • CRMs in the age of data ( web page, slides, pdf, source)
  • Segmentation: between marketing and data science ( web page, slides, pdf, source)
• Module 4. Primers on network analysis and text mining
  • Essential readings on text mining
    Essential readings on network analysis
    
  • A primer on network analysis ( web page, slides, pdf, source)
  • A primer on text mining ( web page, slides, pdf, source)
  Application: segmenting wine buyers with Gephi
  • What is Gephi? ( web, slides, pdf, source)
  • A simple Gephi project from A to Z ( web, slides, pdf, source)
• Module 5. Data-driven value creation and business models based on data
  • Essential readings
    
  • The 7 roads to data-driven value creation ( web page, slides, pdf, source)
  • 3 types of business models centered on data ( web page, slides, pdf, source)
• Module 6. IoT, personalization and localization
  a. The business relevance of IoT
  • Essential readings on IoT
  • Definitions of Internet of Things / connected & smart objects ( web, slides, pdf, source)
  • IoT in manufacturing and logistics by Julien Calviac (video).
    IoT and security by Romain Willmann (video).
  b. Personalization, localization and value creation
  • Essential readings on personalization and localization
  • Personalization and value creation ( web, slides, pdf, source)
  • Localization and value creation ( web, slides, pdf, source)
• Module 7. Data visualization
  • Essential readings
    
  • Data visualization: a personal view point on its past, present and future ( web page, slides, pdf, source)
  • L'intérêt de la visualisation des données pour le business (webinar) par Clément Levallois (video).
    
  • Creating a dataviz for a business app: an interview with Jan Willem Tulp (video).
    
• Module 8. Data Protection and compliance
  • Essential readings on data compliance and ethics
    Essential readings on algorithmic transparency
    Essential readings on algorithmic bias and discrimination
    Essential readings on GDPR
    Essential readings on surveillance and profiling
    
  • Privacy and the protection of personal data ( web page, slides, pdf, source)
  • GDPR and data protection globally ( web page, slides, pdf, source)
• Module 9. Data Science, Machine Learning and Artificial Intelligence
  • Introductory readings on data science
    General introductions to AI
    Essential readings on algorithmic transparency
    Business applications of artificial intelligence
    Essential readings on the future of data science and AI
    
  • Machine learning / data science / Artificial Intelligence explained ( web page, slides, pdf, source)