Download ITECH7406 - fdl Grades

Course Outline
Title:
BUSINESS INTELLIGENCE AND DATA WAREHOUSING
Code:
ITECH7406
Faculty / Portfolio: Faculty of Science and Technology
Program Level:
AQF Level of Program
5
6
7
8
9
10
Level
Introductory
Intermediate
Advanced
Pre-requisites:
(ITECH1104 and ITECH1006 and ITECH5402)
Co-requisites:
Nil
Exclusions:
Nil
Credit Points:
15
ASCED Code:
029999
Learning Outcomes:
This course introduces students to business intelligence and data warehousing techniques
used to analyse enterprise data sets. Topics may include theories and principles of data
warehousing, business intelligence basics, value of DW and BI, relationship between DW
and BI, DW architecture, DW types, designs and characteristics, BI model development, BI
tools and technologies, data modelling, metadata and source data, data conversion,
migration and storage, data quality issues, data mining, data marts, and online analytical
processing.
Knowledge:
K1. Investigate the scope and application of various technologies within a business
intelligence
system context.
K2. Investigate the major approaches to the development of business intelligence and
reporting
systems.
K3. Develop knowledge of the theories and principles of data warehousing.
K4. Understand the potential benefits of data warehousing.
K5. Understand the relationship between business intelligence and data warehousing.
Skills:
S1. Apply business intelligence techniques using an industry standard approach to
explore, extract
and analyse enterprise data sets.
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CRICOS Provider Number: 00103D
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Course Outline
ITECH7406 BUSINESS INTELLIGENCE AND DATA WAREHOUSING
S2. Use complex multi-dimensional databases.
S3. Coordinate data warehouse design, architecture, sourcing, implementation and
governance
approaches to managing data repositories.
Application of knowledge and skills:
A1. Communicate and foster realistic expectations of the role of technology and business
intelligence systems in management and decision support.
A2. Adopt problem solving and decision making strategies to communicate solutions with
key
stakeholders for a variety of issues relating to data warehousing and business
intelligence
solutions.
Values and Graduate Attributes:
Values:
V1. Value the need to work collaboratively and autonomously on business intelligence and
data
warehousing problems.
V2. Appreciate the strategic importance of business intelligence data.
Content:
Topics may include:
•
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•
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theories and principles of data warehousing (DW)
business intelligence (BI) basics
value of DW and BI
relationship between DW and BI
DW architecture
DW types, designs and characteristics
BI model development
BI tools and technologies
Data Modelling
Data conversion, migration and storage
Data quality issues
Data Mining
Data Marts
online analytical processing (OLAP)
Assessment:
This course is delivered in the form of directed
learning activities, lectures and labs/tutorials. Students are encouraged to work
independently and in teams to complete tasks. Learning tasks will be comprised of written
evaluations as well as practical problem based activities.
Learning Outcomes Assessed
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Assessment Task
CRICOS Provider Number: 00103D
Assessment Type
Weighting
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Course Outline
ITECH7406 BUSINESS INTELLIGENCE AND DATA WAREHOUSING
K1,K2,K3,K4;S1,S2,S3
Develop skills in the analysis
Tutorials/Assignment(s)
30%-50%
Examination(s)/Presentation(s)
50%-70%
and practical application of
content introduced
K1,K2,K3,K4;S1,S2,S3
Participate in lectures and
labs/tutorials, read and
summarise theoretical and
practical aspects of the course
Adopted Reference Style:
APA
Presentation of Academic Work:
FedUni General Guide to Referencing
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