Data Warehouses

Code:

EIC0046

Acronym:

ADAD

Keywords
Classification	Keyword
OFICIAL	Information Systems

Instance: 2008/2009 - 1S

Active?	Yes
Responsible unit:	Department of Informatics Engineering
Course/CS Responsible:	Master in Informatics and Computing Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MIEIC	7	Syllabus since 2006/2007	5	-	6	56	162

Teaching language

Portuguese

Objectives

The students should be able to design, build and explore data warehouses.

Program

Data warehouses: selecting dimensions; granularity; fact tables; specific data models; heterogeneity, feeding and data migration strategies; access to large data sets; developing data marts. Multidimensional databases, aggregation and data visualization. Dat warehouses and the Web.

Mandatory literature

Kimball, Ralph 070; The Data Warehouse lifecycle toolkit. ISBN: 0-471-25547-5

Complementary Bibliography

Kimball, Ralph; The data warehouse toolkit. ISBN: 0-471-15337-0
Inmon, W. H.; Building the data warehouse. ISBN: 0-471-08130-2

Teaching methods and learning activities

The lectures are used to present the subject topics illustrated by examples and laboratory work.
To guide the experimental side of learning a few lab assignments are proposed and developed until the final report is discussed.

Software

Oracle 10g Warehouse Builder
Oracle Discoverer

keywords

Physical sciences > Computer science > Database management

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Description	Type	Time (hours)	Weight (%)	End date
Subject Classes	Participação presencial	42,00
Final exam	Exame	3,00
Building a data warehouse	Exame	25,00
	Total:	-	0,00

Amount of time allocated to each course unit

Description	Type	Time (hours)	End date
Self study	Estudo autónomo	25
	Total:	25,00

Eligibility for exams

Distributed evaluation (AD) requires a minimum of 6/20.

Calculation formula of final grade

Mark = round(0,5 AD + 0,5 EF).
Final exam must score more than 7,5.

Examinations or Special Assignments

Medium size lab assignment.

Special assessment (TE, DA, ...)

Follows the general rules.

Classification improvement

The final exam can be improved by a second chance exam.

Observations

Pre-requisites: relational model, SQL, normalization theory.