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Gestión de la Información Digital (19BBA11001)

General information

Type:

OB

Curs:

2

Period:

S semester

ECTS Credits:

4 ECTS

Teaching Staff:

Group Teacher Department Language
Sec: A Joan Rodón Mòdol Operaciones, Innovación y Data Sciences CAT

Group Teacher Department Language
Sec: B Joan Rodón Mòdol Operaciones, Innovación y Data Sciences ESP

Group Teacher Department Language
Sec: C Joan Rodón Mòdol Operaciones, Innovación y Data Sciences CAT

Workload distribution

Workload distribution:
Lectures: 22.5 hours
Participatory sessions: 16.5 hours

COURSE CONTRIBUTION TO PROGRAM

The pervasive digitalization of life has become a new reality of organizations, sectors, and society in general. The capacity of digital technologies to gather, process, store and analyze large amounts of data is not only reshaping the way organizations structure their processes in order produce and deliver products and services, but is also transforming industries giving room for new business models that displace incumbent ones. The overall goal of this course is that students get an understanding and skills related with the use of technologies for storing, retrieving and analyzing digital information.

Course Learning Objectives

The overall goal of this course is that students get an understanding and skills related with the use of technologies for storing, retrieving and analyzing digital information.

CONTENT

1. The foundational properties of digital data

2. The exploitation of relational databases

3. The design of data models

4. The exploitation of non-relational data

Methodology


ASSESSMENT

ASSESSMENT BREAKDOWN

Description %
Individual participation 15
Individual mid-term exam 25
Teamwork 30
Final exam 30

Assessment criteria

The final grade for the course will be based on class participation, mid-term and final exams, and team activities. For each session, students are expected to come prepared for the class. Class attendance is compulsory. Non-attendance can only be justified by program management. The schema for the final grade is as follows:
Individual participation: 15%
Individual mid-term exam: 25%
Teamwork: 30%
Final exam (individual): 30%


To pass the course students must obtain a minimum mark of 4 out of 10 on the mid-term exam and the final exam. The teamwork will involve two graded activities (explained below).

Team activity 1: Debating a topic
We cannot separate the proliferation of new digital business models from certain topics around the ownership and governance of data and the evolution of digital technologies. The purpose of this activity is that students (in teams) prepare and present a topic -for instance, net neutrality, blockchain, personal data banks, data privacy, etc. Each team will be assigned a topic and given some essays written by leaders on the fields of business, economics, law, political sciences, etc. Each team will present the standpoint of the essays being assigned, and the position of the team about the arguments made in those essays. It is also expected that teams encourage the rest of the class to discuss the topic being presented. Each team (or group of teams) will have 30 minutes (for the presentation, discussion, questions, etc.). Presentations will take place in class (see the course website for more details).

Team activity 2: Building a data model for a digital business
Each team will be assigned an existing business and asked to design the data model that support its operations. Each team will have to submit a report with the proposal and give a 10-minute presentation in front of the professor.

There will be a peer evaluation at the end of the course for the teamwork (the two activites). The purpose of the peer review is twofold: (1) for each of you to reflect on how you worked as teams and grade the team members; and (2) to give us (professors) data to adjust evaluations to account for your contribution to your teams. Needless to say that all peer reviews will be confidential and that you cannot assign points to yourself. If any of you have not filled up the peer evaluation by the deadline, we will assume that you consider all team members have contribute equally to the final outcome. Based on the peer evaluation we will obtain a multiplier that we will use to adjust the team grades on an individual basis (capping it up or down a maximum of 20%). Regardless of the peer evaluation, in case the professor finds evidences that the contribution is not evenly distributed among members of a team, the grade of the teamwork might be different across members of a team.

Bibliography

The readings that are required for each session and activity of the course will be posted in the course website. Below there are two references that broadly cover the main contents of the course.
- Dyer, Russell (2009). MySQL in a Nutshell, 2nd Ed. O'Reilly Media, http://shop.oreilly.com/product/9780596514334.do
- Churcher, Clare (2012). Beginning Database Design, 2nd Edition. O'Reilly Publisher, https://www.apress.com/br/book/9781430242093

Timetable and sections

Group Teacher Department
Sec: A Joan Rodón Mòdol Operaciones, Innovación y Data Sciences

Timetable Sec: A

Group Teacher Department
Sec: B Joan Rodón Mòdol Operaciones, Innovación y Data Sciences

Timetable Sec: B

Group Teacher Department
Sec: C Joan Rodón Mòdol Operaciones, Innovación y Data Sciences

Timetable Sec: C