Databases and Information Analysis

Year
2
Academic year
2021-2022
Code
02007957
Subject Area
Informática
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

This course is a course in databases and data analysis. Databases are an essential component of computer systems. Beyond the fundamentals (relational model, normalization, SQL, relational operations), 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.

Work Placement(s)

No

Syllabus

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 to program exploratory data analysis.

Learn to program discovery of new knowledge from data.

Learn to program visualization and report on the data.

Head Lecturer(s)

Pedro Nuno San-Bento Furtado

Assessment Methods

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

Bibliography

Main:

Handouts

R. Ramakrishnan, Johannes Gehrke, Database Management Systems, McGraw Hill, 2002.

Database System Concepts, 5th Edition by Avi Silberschatz, Henry F. Korth, and S. Sudarshan McGraw-Hill International Edition, ISBN: 007-124476-X, May 2005.

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

Other bibliography:

Mastering Python for Data Science, Samir Madhavan, Packt-Book, 2015.

Hector Garcia-Molina, Jeffrey D. Ullman, Jennifer D. Widom, Database Systems: The Complete Book, Prentice Hall, 2001.