Data Warehouses

Code:

EIC0046

Acronym:

ADAD

Keywords
Classification	Keyword
OFICIAL	Information Systems

Instance: 2012/2013 - 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	11	Syllabus since 2009/2010	5	-	6	56	162

Teaching language

Suitable for English-speaking students

Objectives

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

Program

Data warehouses: concept, architecture and approaches; selecting dimensions; granularity; fact tables; specific data models; heterogeneity, feeding and data migration strategies; access to large data sets; developing data marts. Multidimensional modeling. Aggregation and data visualization.

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
Oracle Warehouse Builder - User's Guide, 2008

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 lab assignment is proposed and developed until the final report is discussed.

Software

Oracle

keywords

Physical sciences > Computer science > Database management

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Description	Type	Time (hours)	Weight (%)	End date
Attendance (estimated)	Participação presencial	42,00
Final examination	Exame	3,00
Development of a small data warehouse	Trabalho laboratorial	60,00		2012-12-12
	Total:	-	0,00

Amount of time allocated to each course unit

Description	Type	Time (hours)	End date
Self study	Estudo autónomo	57
	Total:	57,00

Eligibility for exams

Distributed evaluation requires a minimum of 7,5/20.

Calculation formula of final grade

Final Exam: 50%
Lab assignment: 50%

Final exam must score more than 7,5.

Examinations or Special Assignments

Medium size lab assignment.

Special assessment (TE, DA, ...)

Students with special status must deliver and present the lab assignment and answer the examination at the same dates as the other students.

Classification improvement

The final exam can be improved with an Exam for Classification Improvement.
The lab assignment can be improved by a new assignment to be defined by the teacher.

Observations

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