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  2. Business Analytics Applications [SBL2404]

School: Business and Law

This unit information may be updated and amended immediately prior to semester. To ensure you have the correct outline, please check it again at the beginning of semester.

  • Unit Title

    Business Analytics Applications

  • Unit Code

    SBL2404

  • Year

    2027

  • Enrolment Period

    1

  • Version

    1

  • Credit Points

    15

  • Full Year Unit

     N

  • Mode of Delivery

  • Unit Coordinator

    Dr Ahmad KHANFAR

Description

This unit explores the application of business analytics and artificial intelligence (AI) in solving contemporary organisational problems. Students learn how intelligent systems, AI agents, and analytical tools can be implemented to optimise business performance, enhance decision-making, and create competitive advantage. The unit introduces key concepts in AI-driven analytics, data automation, predictive modelling, and digital innovation, with an emphasis on practical applications and case-based learning. By engaging in applied projects, students gain hands-on experience with AI and analytics tools, preparing them to contribute effectively to data-informed strategies and digital transformation initiatives in business environments.

Prerequisite Rule

Students must have passed SBL1402

Learning Outcomes

On completion of this unit students should be able to:

  1. Apply business analytics techniques to address organisational challenges.
  2. Evaluate intelligent systems that support data-driven decision-making.
  3. Apply analytical tools to generate, interpret, and communicate actionable insights.
  4. Assess ethical and responsible practices in the use of AI-enabled technologies.

Unit Content

  1. AI in business analytics.
  2. Intelligent agents and decision support systems.
  3. Data automation and workflow optimisation.
  4. Introduction to machine learning for predictive and prescriptive analytics.
  5. AI-enabled business transformation and innovation.
  6. Ethics, governance, and responsible AI.

Assessment

GS2 GRADING SCHEMA 2 Used for Undifferentiated Pass/Fail units inc. practical units or work-integrated learning

ON CAMPUS
TypeDescription
Portfolio ^Applied Analytics Portfolio
ONLINE
TypeDescription
Portfolio ^Applied Analytics Portfolio

^ Mandatory to Pass

Disability Standards for Education (Commonwealth 2005)

For the purposes of considering a request for Reasonable Adjustments under the Disability Standards for Education (Commonwealth 2005), inherent requirements for this subject are articulated in the Unit Description, Learning Outcomes and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the support for students with disabilities or medical conditions can be found at the Access and Inclusion website.

Assessment

Students please note: The marks and grades received by students on assessments may be subject to further moderation. Informal vivas may be conducted as part of an assessment task, where staff require further information to confirm the learning outcomes have been met. All marks and grades are to be considered provisional until endorsed by the relevant School Progression Panel.

Academic Integrity

Integrity is a core value at Edith Cowan University, and it is expected that ECU students complete their assessment tasks honestly and with acknowledgement of other people's work as well as any generative artificial intelligence tools that may have been used. This means that assessment tasks must be completed individually (unless it is an authorised group assessment task) and any sources used must be referenced.

Breaches of academic integrity can include:

  • Plagiarism: Copying the words, ideas or creative works of other people or generative artificial intelligence tools, without referencing in accordance with stated University requirements. Students need to seek approval from the Unit Coordinator within the first week of study if they intend to use some of their previous work in an assessment task (self-plagiarism).
  • Unauthorised collaboration (collusion): Working with other students and submitting the same or substantially similar work or portions of work when an individual submission was required. This includes students knowingly providing others with copies of their own work to use in the same or similar assessment task(s).
  • Contract cheating: Organising a friend, a family member, another student or an external person or organisation (e.g. through an online website) to complete or substantially edit or refine part or all of an assessment task(s) on their behalf.
  • Cheating in an exam: Using or having access to unauthorised materials in an exam or test.

Serious outcomes may be imposed if a student is found to have committed one of these breaches, up to and including expulsion from the University for repeated or serious acts.

ECU's policies and more information about academic integrity can be found on the student academic integrity website.

All commencing ECU students are required to complete the Academic Integrity Module.

Assessment Extension

In some circumstances, Students may apply to their Unit Coordinator to extend the due date of their Assessment Task(s) in accordance with ECU's Assessment Procedure - for more information visit https://askus2.ecu.edu.au/s/article/000001386.

Special Consideration

Students may apply for Special Consideration in respect of a final unit grade, where their achievement was affected by Exceptional Circumstances as set out in the Assessment Procedure - for more information visit https://askus2.ecu.edu.au/s/article/000003318.

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