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INFO5060: Data Analytics and Business Intelligence (2019 - Summer Main)

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Unit: INFO5060: Data Analytics and Business Intelligence (6 CP)
Mode: Block Mode
On Offer: Yes
Level: Postgraduate
Faculty/School: School of Computer Science
Unit Coordinator/s: Dr Kuan, Kevin
Session options: Summer Main
Versions for this Unit:
Site(s) for this Unit:
Campus: Camperdown/Darlington
Pre-Requisites: None.
Brief Handbook Description: The frontier for using data to make decisions has shifted dramatically. High performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. This course provides an overview of Business Intelligence (BI) concepts, technologies and practices, and then focuses on the application of BI through a team based project simulation that will allow students to have practical experience in building a BI solution based on a real world case study.
Assumed Knowledge: The unit is expected to be taken after introductory courses or related units such as COMP5206 Information Technologies and Systems
Timetable: INFO5060 Timetable
Time Commitment:
# Activity Name Hours per Week Sessions per Week Weeks per Semester
1 Lecture 4.00 2 3
2 Tutorial 2.00 2 3
3 Laboratory 6.00 2 3
4 Presentation 3.00 1 1
5 Project Work - own time 6.00 3
6 Independent Study 3.00 3

Learning outcomes are the key abilities and knowledge that will be assessed in this unit. They are listed according to the course goal supported by each. See Assessment Tab for details how each outcome is assessed.

Unassigned Outcomes
1. Ability to design and implement a business intelligence dashboard solution
2. Thorough understanding of the conceptual foundations and technological underpinnings of data analytics and components of business intelligence architecture
3. Ability to use library databases and search online material
4. Able to provide professional decision-making in developing a business intelligence solution. Exercises sound critical judgement in undertaking a real world Business Intelligence development case study.
5. Experience team work through the team assignments and presentations.
6. Ability to present in-depth on a `customer` on a Business Intelligence Solution. Extensive consideration of theoretical and methodological issues regarding the solution proposed. Able to interpret and discuss issues and situations around the solution with due consideration of broad theoretical/practical context.
Assessment Methods:
# Name Group Weight Due Week Outcomes
1 Participation No 15.00 Multiple Weeks 1, 2, 3,
2 Team Assignment Yes 25.00 Week 3 1, 2, 3, 5,
3 Team Proposal and Presentation Yes 25.00 Week 3 2, 5,
4 Final Exam No 35.00 Week 3 1, 2,
Assessment Description: The team assignment will require students to apply the knowledge and techniques covered in the course to develop a business intelligence solution based on a real world case study. Using an experiential learning approach, each team will use a Business Intelligence methodology to gather business requirements, design a solution and build a working prototype of a performance dashboard. To make the learning dynamic, the lecturer will role play the customer and provide information for the business requirements, and ongoing feedback as the teams’ design and build their solutions. There will be a strong focus on leveraging the industry expertise of the lecturer to coach the teams through the process and soft skills of building a business intelligence solution. The assessment deliverables will be based on both the BI Solution and a presentation.

The final exam will be 1 hour long (with 10 minutes reading time) during the University Examination period. It will consist of 25 multiple choice questions and test the students knowledge of the course core concepts.
Grade Type Description
Standards Based Assessment Final grades in this unit are awarded at levels of HD for High Distinction, DI (previously D) for Distinction, CR for Credit, PS (previously P) for Pass and FA (previously F) for Fail as defined by University of Sydney Assessment Policy. Details of the Assessment Policy are available on the Policies website at . Standards for grades in individual assessment tasks and the summative method for obtaining a final mark in the unit will be set out in a marking guide supplied by the unit coordinator.
Minimum Pass Requirement It is a policy of the School of Computer Science that in order to pass this unit, a student must achieve at least 40% in the written examination. For subjects without a final exam, the 40% minimum requirement applies to the corresponding major assessment component specified by the lecturer. A student must also achieve an overall final mark of 50 or more. Any student not meeting these requirements may be given a maximum final mark of no more than 45 regardless of their average.
Policies & Procedures: IMPORTANT: School policy relating to Academic Dishonesty and Plagiarism.

In assessing a piece of submitted work, the School of Computer Science may reproduce it entirely, may provide a copy to another member of faculty, and/or to an external plagiarism checking service or in-house computer program and may also maintain a copy of the assignment for future checking purposes and/or allow an external service to do so.

Other policies

See the policies page of the faculty website at for information regarding university policies and local provisions and procedures within the Faculty of Engineering and Information Technologies.
Online Course Content:

Note that the "Weeks" referred to in this Schedule are those of the official university semester calendar

Week Description
Week 1 Days 1 & 2 (First teaching block conducted in week 1 of summer semester)

Day 1 (Module 1: Introduction to Data Analytics and Business Intelligence)

• The history of Data Analytics and Business Intelligence

• The business case for Business Intelligence

• Organizational decision making

• Examples of Business Intelligence in Action

• Careers in Business Intelligence

Day 2 (Module 2: Introduction to Dashboards)

• Dashboard Concept

• Dashboard Examples

• SAP Dashboard Design

• Dashboard Tutorial
Week 2 Days 3 & 4 (Second teaching block conducted in Week 2a of summer semester)

Day 3 (Module 3: Dashboard Development Methodology)

• Dashboards and Performance Management

• Identifying and prioritizing Key Performance Indicators

• Fundamentals of Dashboard design

• Usability and dashboard design layout

• Selecting the appropriate media for displaying data

Day 4 (Module 4: BI Solution Architecture)

• Components of a BI Solution

• Data Sources

• Data Integration

• Data Quality

• Data Warehouses

• Reports and Dashboards

Days 5 & 6 (Third Teaching Block conducted in Week 2b of summer semester)

Day 5 (Module 5: Advanced Topics in BI)

• BI Success and Change Management

• BI Capability and Maturity Model

Day 6 (Module 6: Current trends in BI)

• Self Service BI

• Real-Time BI

• Mobility and BI
Week 3 Revision & Presentations
Assessment Due: Team Assignment
Assessment Due: Team Proposal and Presentation
Assessment Due: Final Exam

Course Relations

The following is a list of courses which have added this Unit to their structure.

Course Year(s) Offered
Graduate Certificate in Information Technology 2015, 2016, 2017, 2018, 2019, 2020
Graduate Certificate in Information Technology Management 2015, 2016, 2017, 2018, 2019, 2020
Graduate Diploma in Computing 2015, 2016, 2017, 2018, 2019, 2020
Graduate Diploma in Information Technology 2015, 2016, 2017, 2018, 2019, 2020
Graduate Diploma in Information Technology Management 2015, 2016, 2017, 2018, 2019, 2020
Graduate Certificate in Information Technology Management (till 2014) 2014
Graduate Certificate in Information Technology (till 2014) 2014
Graduate Diploma in Complex Systems 2019, 2020
Graduate Diploma in Information Technology Management (till 2014) 2014
Graduate Diploma in Information Technology (till 2014) 2014
Master of Complex Systems 2019, 2020
Master of Data Science 2016, 2017, 2018, 2019, 2020
Master of Information Technology 2015, 2016, 2017, 2018, 2019, 2020
Master of Information Technology Management 2015, 2016, 2017, 2018, 2019, 2020
Master of IT/Master of IT Management 2015, 2016, 2017, 2018, 2019, 2020
Master of Information Technology Management (till 2014) 2014
Master of Information Technology (till 2014) 2014

Course Goals

This unit contributes to the achievement of the following course goals:

Attribute Practiced Assessed
(6) Communication and Inquiry/ Research (Level 4) No 0%
(7) Project and Team Skills (Level 4) No 0%
(8) Professional Effectiveness and Ethical Conduct (Level 4) No 0%
(5) Interdisciplinary, Inclusiveness, Influence (Level 4) No 0%
(4) Design (Level 4) No 0%
(2) Engineering/ IT Specialisation (Level 4) No 0%
(3) Problem Solving and Inventiveness (Level 4) No 0%
(1) Maths/ Science Methods and Tools (Level 4) No 0%

These goals are selected from Engineering & IT Graduate Outcomes Table 2018 which defines overall goals for courses where this unit is primarily offered. See Engineering & IT Graduate Outcomes Table 2018 for details of the attributes and levels to be developed in the course as a whole. Percentage figures alongside each course goal provide a rough indication of their relative weighting in assessment for this unit. Note that not all goals are necessarily part of assessment. Some may be more about practice activity. See Learning outcomes for details of what is assessed in relation to each goal and Assessment for details of how the outcome is assessed. See Attributes for details of practice provided for each goal.