University of Technology Sydney

26804 Data Driven Decision Making

Warning: The information on this page is indicative. The subject outline for a particular session, location and mode of offering is the authoritative source of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.

Subject handbook information prior to 2024 is available in the Archives.

UTS: Business
Credit points: 3 cp

Subject level:


Result type: Grade and marks

There are course requisites for this subject. See access conditions.


Business analytics is concerned with the use of data, quantitative analysis, predictive models, and evidence-based management to create value for organisations. With the tremendous growth in the amount of data being generated by organisations, government, and society, it is crucial that the leaders of tomorrow understand the proper tools to be able to make evidence-based decisions. In this subject, students are provided with the foundations of business analytics, as well as an introduction to techniques and methods required for data-driven decision-making. Students gain the necessary knowledge to initiate and conduct small scale business analytics projects and professionally communicate their findings to a diverse set of stakeholders.

Subject learning objectives (SLOs)

Upon successful completion of this subject students should be able to:
1. critically evaluate the role of data and data analytics for organizational decision-making
2. synthesise statistical and analytical approaches to derive insights from data
3. visualise and communicate the results of data analyses to inform professional decision-making
4. apply ethical principles to the process of data collection, storage, and usage

Contribution to the development of graduate attributes

The subject introduces students to business analytics and provides a framework for data-driven decision making. It requires students to critically analyse the facts they are presented with to provide a solution to the identified problem(s). The learning activities enable students to develop and apply analytical and presentation skills in complex and diverse contexts.

This subject contributes to the development of the following graduate attributes:

  • Intellectual rigour and innovative problem solving
  • Professional and technical competence

Teaching and learning strategies

This subject is delivered through a mix of online learning, three live online webinars and online consultations. The subject features a mix of theoretical concepts and application in the contemporary context that is designed to apply evidence-based judgement, analytical and creative skills to solve complex business problems.

Students have access to online resources, and self-directed learning activities and are expected to study online content provided via the UTS learning management system. They are required to complete online learning activities, which will help identify knowledge gaps and inform discussions. They are required to engage in online discussions with their peers and academics. Webinars are designed to present the theory and practice of the subject’s content. Students are required to complete pre-work activities before attending webinars. Discussions focus on the application of concepts, techniques, and methods.

A mandatory, on-line formative assessment provides students with further feedback to direct their self-study. Ongoing general and individual feedback will be provided throughout the subject via consultation sessions. A summative assessment provides feedback on students' comprehension and application of learning. Students also receive formal feedback on assessment tasks.

Content (topics)

  • Introduction to business analytics
  • Data exploration
  • Ethical considerations in relation to data
  • Predictive modelling
  • Communication and presentation


Assessment task 1: Data analytics project outline (Individual


This addresses subject learning objective(s):

1, 2 and 4

Weight: 40%
  • Level of detail of the analysis
  • Communication and clarity of the written response
  • Critical articulation of the application of ethics in data analysis

Assessment task 2: Analysis and communication of data (Individual)


This addresses subject learning objective(s):

1, 2 and 3

Weight: 60%
  • Depth and relevance of the analysis
  • Clarity and effectiveness of communication of the findings through verbal and visual mediums

Minimum requirements

Students must achieve at least 50% of the subject’s total marks.


Sahay, A. 2018. Business Analytics, Volume 1: A Data-Driven Decision Making Approach for Business, Business Expert Press

Davenport, T. H., & Harris, J. G. 2007. Competing on Analytics: The New Science of Winning. Harvard Business School Publishing: Boston.

Knaflic, C. N. 2020. Storytelling with Data: Let's Practice. Wiley: New Jersey