Data Warehouse, Data Mining and Business Intelligence

Information and Communication Technologies
5.5 ECTS; 3º Ano, 1º Semestre, 30,0 TP + 30,0 TC

Lecturer

Prerequisites
Average knowledge of numeric methods and statistics

Objectives
At the end of the course, the students should be able to:
.identify the different concepts and methods of data mining
. develop data prediction models based on different techniques.

Program
Introduction
Data; data exploration
Classification - concepts; decision trees; model evaluation; alternative techniques
Association analysis and rules - concepts and algorithms
Grouping analysis - concepts and algorithms
Error detection
Matching analysis
Data mining techniques
Discriminant analysis
Models
Automatic learning

Evaluation Methodology
Test/Exam - 50% of final mark
Practical assignment - 50% of final mark

Bibliography
- H. Witten, I. e Frank, E. (2005). Data Mining: Practical Machine Learning Tools and Techniques. (Vol. 1). (pp. 1-361). San Francisco, USA: Morgan Kaufmann

Method of interaction

Software used in class