Download of 2 COMP 3720 Business Intelligence and Decision Support (3,2,1)

Title (Units):
COMP 3720 Business Intelligence and Decision Support (3,2,1)
Course Aims:
To introduce the concept of business intelligence in the data context of online transaction processing
(OLTP) and online analytic processing (OLAP) and the various techniques used on these data for
information and knowledge in the support of decision making and improved understanding of
operations. Emphasis will be on the understanding and application of enabling technologies for
business intelligence.
Prerequisite:
Year III Standing in Computer Science or Computing Studies
Learning Outcomes (LOs):
Upon successful completion of this course, students should be able to:
No.
1
2
3
4
5
6
7
8
Learning Outcomes (LOs)
Knowledge
Describe business intelligence methodologies and concepts
Explain the characteristics and development of decision support systems
Explain the architectures and construction of data warehouses and data marts
Distinguish between Online Analytic Processing and Online Transaction Processing (OLTP), and identify the different
types of OLAP
Professional Skill
Perform data warehouse and data mart design
Formulate analysis database queries in SQL for analyzing business data
Apply appropriate business intelligence techniques to extract significant business patterns and solve business problems
Attitude
Adopt a receptive yet critical attitude to business information extraction and deployment
Calendar Description:
This course provides a study of business intelligence, the enabling technologies, and the applications
of these technologies for business intelligence, including the analysis and design for data
warehousing, various data mining and knowledge discovery and sharing techniques, and the
applications of the results for decision making and improved operations.
Assessment:
No.
Assessment
Methods
Weighting
1
Continuous
Assessment
40%
Examination
60%
2
Remarks
This will include a mid-semester test, assignments, and a mini-project. The test
will be used to determine the students’ understanding and application of the
methodologies and techniques of business intelligence and decision support, and
is related primarily to learning outcomes 1, 2, and 5. Assignments are designed to
assess the students’ mastery of the techniques and applications of data
warehouses and OLAP and are related mainly to learning outcomes 3, 4, and 6.
The mini-project is designed to achieve learning outcomes 5, 6, 7, 8, by requiring
students to work in a team environment to design and implement creative
solutions through the application of the methodologies learned.
The final examination is designed to measure the extent to which students have
reached all of the learning outcomes, apart from outcome 8 which is assessed in
the mini-project. Students are required to have a good mastery of the concepts,
methodologies, and applications of business intelligence and decision support
techniques to familiar as well as novel business situations and problems.
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Learning Outcomes and Weighting:
Content
I The Business Intelligence Perspective
II Business Intelligence Enabling Technologies
III Business Intelligence Applications
Project
References:
LO No.
1, 7
2, 3, 4, 5
3, 6, 7, 8
5, 6, 7, 8
Turban, E., Aronson, J., Liang, T., and Sharda, R. Decision Support and Business
Intelligence Systems. 8th Edition, Addison-Wesley, 2007
Inmon, W. H. Building the Data Warehouse. 4th Edition, Wiley, 2005.
Course Content in Outline:
Topic
I.
Business Intelligence
A. Overview
B. Framework – OLTP and OLAP
II.
Business Intelligence Enabling Technologies
A. Data warehousing
B. Data mining and techniques
C. Decision support techniques
D. Intranet web
E. Business intelligence software
F. Other state-of-the-art technologies
III.
Business Intelligence Applications
A. Business applications such as supply chain management, customer relationship management,
enterprise resources planning
B. Decision support
C. Process intelligence
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