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Unit of study_

INFS3050: Business Intelligence for Managers

Semester 2, 2022 [Normal day] - Camperdown/Darlington, Sydney

To gain or maintain their competitive edge, more than ever before, organisations need to rely on high-quality information to support decision making processes at all organisational levels. Business Intelligence (BI) is now being recognised as one of the top business priorities world-wide. While in the past, the term BI was used to describe a very broad range of software applications, the latest thinking in this field emphasises IS support for human intelligence, in the context of business decision making. In this unit, students learn how BI helps information discovery and how to analyse multidimensional data. Students gain hands-on experience in using a commercial BI platform. These practical skills, combined with in-depth analytical skills enable students to assist any organization (regardless of its size and industry domain) to derive more intelligence from its data, improve its performance and ultimately, compete on analytics. Issues are explored from the business rather than the technology perspective. This unit does not require prior programming experience.

Unit details and rules

Unit code INFS3050
Academic unit Business Information Systems
Credit points 6
Assumed knowledge

INFS1000 or INFO1000 or INFO1003 or INFO1903

Available to study abroad and exchange students


Teaching staff

Coordinator Petri Hallikainen,
Type Description Weight Due Length
Final exam (Record+) Type B final exam Final exam
30% Formal exam period 2 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5
Assignment group assignment Tutorial work 1
Tableau tutorial 1
3% Week 05 n/a
Outcomes assessed: LO3
Assignment group assignment Tutorial work 2
Tableau tutorial 2
7% Week 06 n/a
Outcomes assessed: LO3
In-semester test (Record+) Type B in-semester exam Mid-semester exam
30% Week 07
Due date: 17 Sep 2022 at 14:00
1 hour
Outcomes assessed: LO1 LO2 LO4 LO5
Assignment group assignment Practical assignment
Analysing the BI process and data visualisation using Tableau
30% Week 11
Due date: 21 Oct 2022 at 23:59

Closing date: 23 Oct 2022
2500 words
Outcomes assessed: LO1 LO4 LO3
group assignment = group assignment ?
Type B final exam = Type B final exam ?
Type B in-semester exam = Type B in-semester exam ?

Assessment summary

  • Tutorial work 1 and 2: Students are expected to demonstrate the understanding of the basics of using Tableau and designing a visualisation solution. The tutorials are done during normal class time and must be submitted by the end of the class time.
  • Mid-semester exam: This exam tests the understanding of the foundational business intelligence concepts.
  • Practical assignment: Students are required to develop a data visualisation solution to address a business problem using Tableau. A data set will be provided to students. Each group will present their results in the Zoom/Campus sessions on week 12.
  • Final exam: The final exam tests the understanding of business intelligence concepts and frameworks in an organisational context. This exam covers all the unit materials.

Detailed information for each assessment can be found on Canvas.


Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range


High distinction

85 - 100

Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard, as defined by grade descriptors or exemplars outlined by your faculty or school. 


75 - 84

Awarded when you demonstrate the learning outcomes for the unit at a very high standard, as defined by grade descriptors or exemplars outlined by your faculty or school.


65 - 74

Awarded when you demonstrate the learning outcomes for the unit at a good standard, as defined by grade descriptors or exemplars outlined by your faculty or school.


50 - 64

Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard, as defined by grade descriptors or exemplars outlined by your faculty or school. 


0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website  provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.  

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Week 01 Introduction to unit of study Seminar (3 hr) LO1 LO2 LO4 LO5
Week 02 Foundations for understanding business intelligence Seminar (3 hr) LO1 LO2 LO4 LO5
Week 03 Data Warehousing: the business perspective Seminar (3 hr) LO1 LO2 LO4 LO5
Week 04 Data quality and value of information Seminar (3 hr) LO1 LO2 LO4 LO5
Week 05 Information discovery and decision making Seminar (3 hr) LO1 LO2 LO4 LO5
Week 06 Designing business intelligence solutions Seminar (3 hr) LO1 LO3
Week 07 1. Preparation for the mid semester exam. 2. Comprehensive case discussion. Seminar (3 hr) LO1 LO2 LO4 LO5
Week 08 Mid-Semester Exam Seminar (1 hr) LO1 LO2 LO4 LO5
Week 09 1. Multi-dimensional modeling and OLAP 2. Ethics Seminar (3 hr) LO3 LO4
Week 10 1. Business performance management: the role of business intelligence; 2. Data visualisation Seminar (3 hr) LO3 LO4
Week 11 Group project work and consultations Seminar (3 hr) LO1 LO3 LO4
Week 12 Group presentations Seminar (3 hr) LO1 LO3 LO4
Week 13 Preparation for the final exam Seminar (3 hr) LO1 LO2 LO3 LO4 LO5

Attendance and class requirements

Lecture recordings: Lectures and seminars are recorded and will be available on Canvas for student use. 

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

All readings for this unit can be accessed through Canvas.

The following textbook is recommended for background reading:

  • Sharda, R., Delen, D. and Turban, D. (2014). Business intelligence: A managerial perspective on analytics (3rd Global ed.). Pearson International Edition.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. use appropriate conceptual frameworks to analyse the role of different business intelligence applications in supporting day to day business and improving organisational and competitive advantage
  • LO2. describe the organisational issues related to a business intelligence based management approach and propose solutions to overcome the issues
  • LO3. design a business intelligence solution to address a business problem using a commercial business intelligence platform
  • LO4. relate business intelligence to business performance management, business process management and information management in an enterprise
  • LO5. demonstrate an awareness of the current and emerging trends in business intelligence.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities

This section outlines changes made to this unit following staff and student reviews.

Some improvements have been made to the unit design since this unit was last offered.
  • Tableau licence: Licences for using Tableau will be provided to students.


The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.