Databases and Information Analysis

Year
0

Academic year
2026-2027

Code
02007957

Subject Area
Biomedical Engineering

Language of Instruction
Portuguese

Other Languages of Instruction
English

Mode of Delivery
Face-to-face

Duration
SEMESTRIAL

ECTS Credits
6.0

Type
Elective

Level
2nd Cycle Studies - Mestrado

Recommended Prerequisites

Basic programming.

Teaching Methods

Exposition of subjects and questions in the theoretical class: consists of classes organized for each subject of the syllabus, always associated with representative examples and their connection to the practical world.

Practical exploration in hands-on classes: Hands-on lessons are organized as a set of prepared question sheets that are challenging steps to answer through the use of computer tools. The teacher lets the students try to come up with the solution, supports and helps, and then demonstrates how to reach that solution.

Project and its accompaniment.

Learning Outcomes

Learn how to define a database for a problem correctly.

Learn how to query and manage the data in a database.

Learn to use practical tools for those operations.

Learn NoSQL and DB development tools.

Learn to program exploratory data analysis.

Learn to program discovery of new knowledge from data.

Learn to program visualization and report on the data.

Work Placement(s)

Syllabus

This course is a course in databases and data analysis. Databases are an essential component of computer systems. Beyond the fundamentals (relational model, SQL, entity-relationship), one learns to operationalize the analysis, design and construction of databases. The ability to analyze data, discover trends and visualize them enables organizations to innovate and increase productivity. Besides data analysis concepts (exploratory analysis, statistics, knowledge discovery and visualization), one learns to operationalize this analysis using a programming language, with emphasis also to how databases and analysis are intertwined.

Head Lecturer(s)

Pedro Nuno San-Bento Furtado

Assessment Methods

Assessment
Resolution Problems: 10.0%
Project: 30.0%
Exam: 60.0%

Bibliography

Main:

Handouts

Ramez Elmasri, Shamkant Navathe. Fundamentals of Database Systems 7th Edition, eds. Pearson, 2015.

Vanderplas, J. Python Data Science Handbook - Essential Tools for Working with Data, 2022.

Django 5 By Example - Fifth Edition, Antonio Melé, ed packt, 2024.

Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data. EMC Education Services (Editor). ISBN: 978-1-118-87613-8, January 2015.