Course Title: Business Data Analytics

Part A: Course Overview

Course Title: Business Data Analytics

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

ECON1555

City Campus

Postgraduate

660H Graduate School of Business and Law

Face-to-Face

Sem 1 2020,
Sem 2 2020

ECON1556

RMIT University Vietnam

Postgraduate

660H Graduate School of Business and Law

Face-to-Face

Viet1 2020,
Viet2 2020,
Viet3 2020

ECON1557

RMIT Vietnam Hanoi Campus

Postgraduate

660H Graduate School of Business and Law

Face-to-Face

Viet3 2020

Flexible Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

ECON1348

RMIT Online

Postgraduate

660H Graduate School of Business and Law

Internet

JulDec2019 (KP6)

ECON1348

RMIT Online

Postgraduate

660H Graduate School of Business and Law

Internet

JanJun2020 (KP3)

ECON1348

RMIT Online

Postgraduate

660H Graduate School of Business and Law

Internet

JulDec2020 (KP6)

Course Coordinator: Dr Saima Ahmad

Course Coordinator Phone: +61 3 9925 8182

Course Coordinator Email: saima.ahmad@rmit.edu.au

Course Coordinator Location: Melbourne


Pre-requisite Courses and Assumed Knowledge and Capabilities

Assumed Knowledge: BUSM4154 Financial Analytics for Managerial Decisions


Course Description

In the current digital disruption environment, digital capability, particularly the ability to develop insights and business intelligence based on complex data analytics, is becoming an essential skill for contemporary managers. Cutting-edge companies in every industry are using analytics to replace intuition and guesswork in their decision-making to gain competitive edge. The future of work requires managers to have the ability to work with voluminous data and confidently make data-based decisions. 

This course is designed to equip students with methodologies and tools to identify, research and analyse business problems in the digital era. You will study key research paradigms and qualitative and quantitative methods, to unpack business problems. You will learn how to gather useful data from various sources and implement descriptive, predictive and prescriptive analytics to analyse data. You will also explore processes of analytics to allow you to apply algorithms and methodologies to business problems and develop innovative solutions.

This course also covers issues and challenges related to collecting, storing and analysing business data. These include theories and concepts from legal and ethical aspects of business venturing, intellectual property, and ethical and privacy aspects of data. This will enable you to utilise data-driven methods to test the feasibility of opportunities and innovations.


Objectives/Learning Outcomes/Capability Development

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On successful completion of this course you will be able to: 

CLO1: Research and critique business problems using a suitable paradigm and associated methodologies and methods.

CLO2: Analyse business data by applying data analytics techniques and models to develop business intelligence. 

CLO3: Interpret business data and generate ethical and innovative solutions based on data analytics results. 

CLO4: Communicate business solutions professionally and effectively to a varied set of stakeholders. 


Overview of Learning Activities

This course is offered at multiple locations employing different learning modes. This means that the nature of the learning activities may vary depending on where you are enrolled.

In this course you will be encouraged to be an active learner. Your learning will be supported through various in-class and online activities comprising individual and group work. These may include quizzes; assignments; prescribed readings; sourcing, researching and analysing specific information; solving problems; conducting presentations; producing written work and collaborating with peers on set tasks or projects.

You will engage in research by means of searching texts, internet resources and journals (academic and professional). You will use Excel and other statistical software to analyse data. The use of examples places business analytics techniques in context and teaches students how to avoid the common pitfalls, emphasising the importance of applying proper business analytics techniques.


Overview of Learning Resources

Various learning resources are available online through MyRMIT Studies\Canvas. The lecture notes and workshop notes are posted on Canvas.

Resources are also available online through RMIT Library databases and other facilities. Visit the RMIT library website for further details. Assistance is available online via our chat and email services, face to face at our campus libraries or via the telephone on (03) 9925 2020.

Additional resources and/or sources to assist your learning will be identified by your course coordinator and will be made available to you as required during the teaching period. 


Overview of Assessment

The assessment tasks, their weighting and the course learning outcomes to which they are aligned are as follows:

Assessment Task 1: 20%
Linked CLOs: 1, 2, 3

Assessment Task 2: 30%
Linked CLOs: 1, 2, 3, 4

Assessment Task 3: 50%
Linked CLOs: 1, 2, 3, 4

Feedback will be provided throughout the semester in class and/or in online forums through individual and group feedback on practical exercises and by individual consultation.