Advanced Topics in Databases

Code:

CC4007

Acronym:

CC4007

Level:

400

Keywords
Classification	Keyword
OFICIAL	Computer Science

Instance: 2021/2022 - 2S

Active?	Yes
Web Page:	http://www.dcc.fc.up.pt/~michel/aulas/TABD/tabd1415.html
Responsible unit:	Department of Computer Science
Course/CS Responsible:	Master in Computer Science

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
M:CC	27	Study plan since 2014/2015	1	-	6	42	162
M:DS	5	Official Study Plan since 2018_M:DS	1	-	6	42	162
M:ECAD	0	Study plan since 2021/2022	2	-	6	42	162
M:SI	5	Study plan since 2020/2021	1	-	6	42	162

Teaching language

English

Objectives

Learn advanced concepts of Databases, which include the use of relational databases in an environment of generic programming languages. Students learn with special emphasis the "Application Programming Interfaces" APIs in C language of database management systems such as MySQL. They develop the ability to augment such systems through modules written in C.
The concept of deductive database and knowledge representation systems is addressed.
Spatial database concepts are also learned by studying the PostGIS module. You learn SQL with spatial extensions. Various spatial information analysis and visualization tools are used, through the Python programming language and modules such as MatPlotLib.
You learn Data Warehousing concepts and advanced aggregation operators.
NoSQL database concepts are learned.

Learning outcomes and competences

Advanced manipulation of databases, with the ability to manage relational database systems through generic programming languages.

Competence in modelling and querying spatial databases.

Spatial SQL and advanced indexing techniques.

Modeling and querying of datawarehouses.

noSQL databases modelling and implementation.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Previous course on databases (relational model and SQL).

Programming languages, namely C and Python.

Program

Use of relational databases in programming languages environments.

Implementation of databases.

Distributed databases.

Knowledge-base databases.

Spatial databases. Concepts, modellign and multi-dimensional indexing.

Data warehousing.

Multi-dimensional aggregation operators. Cube by.

Novel types of databases and noSQL databases.

 

Mandatory literature

Rigaux Philippe; Spatial databases. ISBN: 978-1-55860-588-6 hbk
Shekhar Shashi 1963-; Spatial databases. ISBN: 978-0-13-017480-2 hbk
DuBois Paul 1956-; MySQL. ISBN: 0-672-32673-6
J.D. Ullman; Principles of database and knowledge - base systems. ISBN: 0-7167-8162-X

Teaching methods and learning activities

Theoretical classes with strong laboratorial component. 

Implementation of exercises exemplifying the theoretical concepts. 

Use of very large datasets in the exercises.

Study of documentation of relational database systems, such as MySQL and PostGres and their C APIs.

Use of presentation slides prepared by the lecturer.

Evaluation Type

Distributed evaluation without final exam

Assessment Components

designation	Weight (%)
Apresentação/discussão de um trabalho científico	10,00
Trabalho prático ou de projeto	40,00
Exame	50,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Frequência das aulas	42,00
Apresentação/discussão de um trabalho científico	10,00
Estudo autónomo	80,00
Trabalho laboratorial	30,00
Total:	162,00

Eligibility for exams

Frequency of laboratorial classes.

Calculation formula of final grade

practical assignment (40%) + presentation (10%) + final exam (50%)