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

Business Intelligence

Description
In the current environment of rich data, it is essential to understand how they generate the knowledge that allows a business to be developed. Modern business management considers the possibilities that a correct data exploitation and management process offers for decision making. Better answers to common questions or new questions to business challenges are possible today thanks to data science applied to management. This subject is specially designed for the MUDS program at La Salle-URL and, therefore, for professionals with or without direct experience in the field of business management. The course will combine different methodologies with the goal that the participants acquire their own criteria, providing applicable knowledge in the immediate future. Management is not an exact science that can be separated from the moment and its context, and therefore the aim is not only to expose the concepts and best current professional practices, but also for the participants to acquire and stimulate their management skills in this area. And the best way to acquire a skill is to practice it, which will be done mainly through cases and discussions. Each case and example is a description of real business situations, and these are meant to serve as a metaphor for a set of problems. The real situations that you will face as professionals may not be the metaphors that have been chosen with the specific cases of the subject, but taken all together, they provide a useful and relevant set of metaphors for different situations, since they present a wide range type of products and companies. The analysis of all these different situations and the capacities that will be developed, detailed later, are relevant for all professionals.
Type Subject
Optativa
Semester
Second
Credits
5.00
Previous Knowledge
Objectives

The goals will focus on:
• Become familiar with the basic concepts of Business Intelligence from the perspective of management, that is, knowing how to capture the knowledge offered by data analysis for decision making, as well as with the main applications of new data analysis techniques in business redesign.
• Within the field of management, develop skills to understand business challenges and transfer it to the search and interpretation of relevant data that allow the making and implementation of decisions that allow directing and transforming the business.
• Finally, the specification of all this in a transformation plan based on data based on the sector of activity.

Contents

SYLLABUS
1. Introduction to the subject and concepts of Business Intelligence
2. DMM Data Maturity Management
3. Big Data
4. Reading the market and the environment
5. Presentations

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

Methodology

The usual dynamics of the course will be "learning by doing", alternating the master class, the practical examples and exercises, and the discussion of cases.
• The master class will emphasize the basic principles and concepts of the area, providing the necessary conceptual frameworks to understand the subject in question. The transparencies used during the session will be distributed as course material.
• The practical examples and/or exercises will complement the theme of each session with the applied vision of the best professional practices of the moment.
• Case discussions are an opportunity to jointly discuss the main concepts of the course. The best way to prepare is to try to solve the proposed questions of the case. When the debate begins in class, you will have to be prepared to provide constructive input to the rest of your classmates as the discussion progresses. View this discussion as an opportunity to discover other points of view and to demonstrate your understanding of the topic at hand.
What this course will give you is directly related to how you go about this process. The best recommendation is that the more they have prepared it, the more they will learn.

Evaluation

Continuous assessment
This subject will be evaluated continuously based on exercises, assignments, practices and presentations in class.

Evaluation Criteria

Continuous assessment
This subject will be evaluated continuously based on exercises, assignments, practices and presentations in class.
The final grade will be a weighting of:
1. Resolution of group cases with individual presentation: 70%
Each team must deliver the resolution of the 4 cases before the presentation session. It is recommended that the format include the following:
o Presentation of the main issue to be resolved in the case.
o Questions of the case (main part of the resolution): it will be necessary to answer each question formulated, stating the pros and cons, and provide a definitive answer considering the data provided.
o Recommendations based on responses made
It is recommended to be coherent in the analysis, concise in the response, relevant in the contributions and decisive in the recommendations.

2. Participation in class: 30%
The evaluation of the participation is necessarily subjective but will be based on its quality. Specifically, the comments are expected to be of reflection and knowledge of the topic, relevant to the discussion, synthetic and consistent, clear, and well-founded of the developments of the teams to be carried out in the sessions.

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:
https://www.salleurl.edu/en/copies-regulation
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. Some references:
• Class notes
• Amazon Case “Amazon’s Big Data Strategy” ICMR 914-005-01
• Netflix case “Netfilx, leveraging Big Data to predict entertainment hits” ICMR 913-006-01
• C.E.O.E. “Digital Plan 2025, the digitization of Spanish society”

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

Additional Material

Additional bibliography:
• Kaplan, Robert S. & Norton, David P.: The Balanced Scorecard, Ed. Management 2000, 1997.
• Porter, Michael: Competitive Advantage, Ed. CECSA, 1988.
• Big Data For Dummies Published by John Wiley & Sons, Inc. 111 River Street Hoboken, NJ 07030-5774 www.wiley.com Copyright © 2013 by John Wiley & Sons, Inc., Hoboken, New Jersey