Bases de Dados II

Base Knowledge

NA

Teaching Methodologies

In this curricular unit, the following teaching methodologies are used:

 

1 – Expository method: explanatory method where theoretical foundations and concept are presented by the teacher and discussed with the class, followed by demonstrative examples;

 

2 – Experimental method: active method where the student develops knowledge through problem solving and the development of individual laboratory projects or in group dynamics.

 

Learning Results

It is expected that at the end of the course the student will be able to:

 

1. Understand the physical aspects of databases and acquire skills for their administration;

 

2. Understand and apply data exploration and analysis techniques;

 

3. Design and develop approaches for data transformation and analysis;

 

4. Programming in a database server using PL/SQL language.

 

Program

1. Physical Aspects of Databases (Structure of a DBMS; Physical parameters; Indexing; Clusters; Hashing; Table and index partitioning; Partitioning methods and keys; Management of table partitions and Sub-Partitioning);

 

2. Introduction to Data Analysis (OLAP, ROLAP AND MOLAP; Data Warehousing; Multidimensional Databases; ETL Process; Data Preparation; Data Mining Concepts);

 

3. Programming in the Database Server (Data Types, Structures, Exceptions, Cursors, Triggers, Procedures, Functions and Packages).

 

Grading Methods

Final evaluation
  • - an individual project with presentation - 50.0%
  • - an individual written test - 50.0%
Periodic Evaluation
  • - a project (individual or in group) with presentation - 35.0%
  • - two individual practical assignments - 65.0%

Internship(s)

NAO

Bibliography

“Database Systems: The Complete Book”; Hector Garcia-Molina; Prentice Hall; ISBN: 933251867X; 2014

“Oracle Database 12c PL/SQL Programming”, Michael McLaughlin ; McGraw-Hill Osborne Media; ISBN: 9780071812436; 2014

“The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling”; Ralph Kimball, Margy Ross; J. Wiley & Sons; ISBN 1118530802; 2013

“Data Warehousing – Conceitos e Modelos”; Carlos Caldeira; Edições Silabo; ISBN 9789726186960; 2012

“Data Mining: Practical Machine Learning Tools and Techniques”, 4.ª Edição; Ian H. Witten, Eibe Frank; Morgan Kaufman; ISBN 0128042915; 2016

“Extracção de conhecimento de Dados”, 3.ª Edição; João Gama et al; Edições Sílabo; ISBN 9789726189145; 2017

Manuais do Oracle disponíveis em  https://docs.oracle.com.