Master of Science in Data Science La Salle Campus Barcelona URL

Master of Science in Data Science

Become an expert in analysing, structuring, filtering, visualizing and valuing the production of generated data

Data and Business

‘Data and Business’ provides you with an analysis of what you need to turn a business/company into a data science organization, oriented to make critical decisions based on data. Under the umbrella of Data Science different concepts are housed: Analytics, Artificial Intelligence, Big Data, techniques that will be applied with a business point of view. You will practice outstanding cases such as Amazon, Disney, Netflix, etc. At the end of the course, you will have used the Artificial Intelligence Canvas and you will have learned techniques to implement a new paradigm of making decisions.
Type Subject
Primer - Obligatoria

Titular Professors

Previous Knowledge

The goals will focus on:
• Understand that it is a data-based organization and what benefits it brings
• Identify the impact of artificial intelligence and data science on business
• How to implement a data-based project


1. Big Data and Data Science in Business
a. Definition
b. Big Data before Big Data
c. Data Science
d. Thinking like a Data Scientist
e. Cognitive Biases
f. Data Visualization

2. Artificial Intelligence for Business
a. How Does Artificial Intelligence Work in a Company?
b. Spotify’s Recommendation System
c. Artificial Intelligence at Netflix
d. Creating House of Cards

3. Big (Brother) Data
a. Beyond the Tip of the Iceberg
b. Data Brokerage and Consumers
c. Predictive Analytics at Facebook
d. Big Data at Tinder – The Big Lies People Tell

4. Finding the Evidence in Business
a. Causality
b. Instrumental variables
c. Natural experiments
d. Regression discontinuity
e. A/B Testing
f. Running Experiments
g. How Obama raised $60 Million?

5. Business with Geolocated data
a. Predicting human movement
b. Retail location
c. Mobile phone data

6. AI Business Model Canvas
a. Presentations

Note: Topics can be adjusted and/or modified at the discretion of the master's coordination.


The methodology used combines master classes, student participation, exercises, and practices. For the student, this will involve both individual and group works, as well as conceptual exercises, written exercises, and oral presentations.


This subject will be assessed on a continuous via from exercises, assignments, practices, and presentations in class.

Evaluation Criteria

Continuous assessment
This subject will be assessed on a continuous via from exercises, assignments, practices, and presentations in class. The final grade will be a weighting of:
- Written exercise: 30%
- Participation: 10%
- Project: 40%
- Oral presentation: 20%

Extraordinary call
The exam and/or works of extraordinary call will be determined from the coordination of the subject.

Copies regulations
The subject is governed by the general regulations of copies of La Salle Campus BCN:
The training activities will be considered to have the following category:
• Exercises: moderately significant
• Project: highly significant
• Final Evaluation: highly significant

Basic Bibliography

The bibliography will be detailed throughout the course:

• Class/Lecture notes
• Documentation and papers uploaded to Intranet (eStudy)
• Hadley Wickham - R for Data Science: Import, Tidy, Transform, Visualize, and Model Data (2021)
• Laudon, Kenneth C. and Laudon, Jane P. (2014). Management Information Systems: Managing the Digital Firm. Global Edition. 13th edition.
• Davenport, T & Harris, J. Competing on Analytics: The New Science of Winning (2014, 2017). Havard Business School
• Foster Provost and Tom Fawcett. Data Science for Business. O'Reilly (2013).
• Carl Anderson. Creating a Data-Driven Organization. O'Reilly. (2015).
• DJ Patil. Building Data Science Teams. O'Reilly. (2011).
• DJ Patil and Hilary Mason. Data Driven: Creating a Data Culture. O'Reilly. (2015).

Additional Material

All class material (presentations, exercises, articles, documents, etc.) will be shared in the subject folder of the La Salle Intranet: eStudy.