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Business Analytics (ISYS30008)
Undergraduate level 3Points: 12.5Not available in 2019
Overview
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Aims
Business analytics involves the use of data to support business decision-making. Topics covered include business decision-making, evidence-based management, data warehouse design and implementation, data sourcing and quality, on-line analytical processing (OLAP), dashboards and data mining, case studies of business analytics practice. This subject is a 3rd year breadth subject in information systems, and forms one of the elective subjects for the Diploma of Informatics.
Indicative Content
This subject introduces the concepts of business analytics, decision making, data warehouse design, data warehouse modelling, data quality, data warehouse implementation - including the ETL process, and data warehouse use in supporting business analytics – including decision making tools and OLAP. Readings are provided for all topics that introduce real world cases on business analytics and related areas and include the use of business analytics in organisations.
Intended learning outcomes
Intended Learning Outcomes (ILOs)
On completion of this subject the student is expected to:
- Be familiar with business analytics and its relationship to decision-making
- Understand the main concepts underlying data warehouse design and implementation, data quality and retrieval and analysis of data
- Be familiar with the use of business analytics in practice
Generic skills
On completion of this subject, students should have developed the following generic skills:
- High level of development: collaborative learning; problem solving; team work; interpretation and analysis; critical thinking
- Moderate level of development: oral communication; written communication
Last updated: 19 March 2024
Eligibility and requirements
Prerequisites
Achieving at least 75% in a programming competency test OR one of the following:
Code | Name | Teaching period | Credit Points |
---|---|---|---|
ISYS10001 | Foundations of Information Systems | Semester 2 (On Campus - Parkville) |
12.5 |
COMP10001 | Foundations of Computing |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
ACCT10003 | Accounting Processes and Analysis | No longer available | |
INFO20003 | Database Systems |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 19 March 2024
Assessment
Additional details
- One group based case study in data warehouse design (25%) with two group members of approximately 2000 words due mid-semester, requiring approximately 26-28 hours of work per student. Intended Learning Outcome (ILO) 2 is addressed in the case study.
- One team based analytical report based on a case study (25%) with 2 team members of approximately 2000 words, requiring approximately 26-28 hours of work per student. ILOs 1 and 3 are addressed in the analytical report.
- One written 2 hour closed book end of semester (50%). ILOs 1 to 3 are addressed in the examination. The examination is a hurdle and must be passed to pass the subject.
Hurdle requirement: To pass the subject, students must obtain:
- at least 50% of the marks available in the non examination based assessment
- at least 50% of the marks available in the examination.
Last updated: 19 March 2024
Dates & times
Not available in 2019
Time commitment details
170 hours
Last updated: 19 March 2024
Further information
- Texts
Prescribed texts
None
- Subject notes
Learning and Teaching Methods
The subject will be delivered through a combination of lectures and labs. Students will also complete two assignments which will reinforce the material covered in class.
Indicative Key Learning Resources
All required readings are available via the LMS.
Careers/Industry Links
This subject is relevant to careers in data warehousing, data analysis, data mining, and information management.
- Breadth options
This subject is available as breadth in the following courses:
- Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
Additional information for this subject
Subject coordinator approval required
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 19 March 2024