Information Systems II

Base Knowledge

Databases

Teaching Methodologies

Powerpoint slides and some demonstration vídeos, complemented with application exercices
Problem resolution
Small project implementation based on development tools

Learning Results

Goals:
Global vision about Information Systems
Planning and management os ISs
Knowledge and application of data warehouses and OLAP modelling and techniques.
Basic knowledge about data mining
Basic knowledge abour discrete simulation as a decision support tool
Particular Information Systems. E-learning, e-commerce, international issues
Development of criticizing skills
Skills:
Planning and management of IS projects
Know when and how to apply Businees Intelligence technologies and models

Program

Baisc knowledge about ERPs and BI
SCM and CRM

Introducion to data warehouses and OLAP
Facts and dimensions
Star and snowflake
Granularity
Hierarquies
Drill down, Rollup, pivot tables and other operations
ETL
OLAP, ROLAP and MOLAP
Implementation using Microsoft BIDS (Visual Studio + SQL Server 2008 R2) + Excel

Introduction to data-mining
General view
Algoritms
Classification
Introduction to classifiers (decision trees, rules, KNN, Bayesian, Neural networks)
Performance
Clustering (k-means)
association (a-priori)
Linear regression
Implementation using Microsoft BIDS (Visual Studio + SQL Server 2008 R2)

Project Management
I
Introduction to Discrete Simulation
Concept
Applications
Architectures
Developing environments
Applications
Implementation of simple models using ExtendSIM

Knowledge Management in organizations
Concept
Knowledge types
Knowledge management cycle

Curricular Unit Teachers

Internship(s)

NAO