University of Technology Sydney

220700 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: 6 cp

Subject level:


Result type: Grade and marks

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


With the advancement of technology, the amount of data generated globally continues to grow enormously. Knowing how to utilise this data to make evidence-based decisions is vital for leaders of tomorrow. This subject provides learners with the tools and understanding necessary to use data in making evidence-based decisions as well as the ethical considerations in regard to the collection, storage and use of data. Learners learn about different types of analyses, predictive models and fact-based management to create value for organisations.

Subject learning objectives (SLOs)

Upon successful completion of this subject students should be able to:
1. Understand the role of data analytics for an organisation
2. Demonstrate methods to locate, prepare and analyse data in order to identify business problems and make predictions
3. Communicate the results of a data analytics project
4. Review ethical principles as they relate to the collection, storage and use of data by organisations

Contribution to the development of graduate attributes

This subject contributes to the development of the following graduate attribute(s):

  • Intellectual rigour and innovative problem solving
  • Communication and collaboration

This subject also contributes specifically to develop the following Program Learning Objective(s) in the Master of Business Administration:

  • Apply critical thinking and advanced analytical skills to develop innovative solutions that address strategic business issues in complex contexts (1.1)
  • Communicate ideas, decisions and strategies clearly and apply interpersonal skills that are sensitive to Indigenous peoples and other diverse peoples, cultures and contexts (2.1)

Teaching and learning strategies

This subject is delivered completely online with a number of live online sessions to discuss any issues in relation to content and assessment tasks. Students are expected to complete a range of different learning activities throughout the week. Activities provide opportunities to learn, apply and discuss the knowledge gained in a practical manner. Feedback is provided from both peers and teaching staff throughout the various activities. You are encouraged to actively provide feedback and interact with staff and students.

Content (topics)

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


Assessment task 1: Context and Ideation (Individual)


This addresses subject learning objective(s):

1, 2 and 4

Weight: 30%

750 words, excluding references

  • Completeness of the proposed data analytics process, including ethical considerations
  • Coherent communication and clarity of the report
  • Relevance and clarity of articulation of data set refinements
  • Completeness of the preliminary analysis of the identified target variable

Assessment task 2: Data Analytics Report (Individual)


This addresses subject learning objective(s):

2 and 3

Weight: 40%

1000 words, excluding references

  • Suitability of data techniques and analytical methods chosen
  • Depth and rigor of the data analysis
  • Coherent communication and clarity of the discussion
  • The coherence and salience of the insights

Assessment task 3: Data Analytics Presentation (Individual)*


This addresses subject learning objective(s):

1, 2, 3 and 4

Weight: 30%

6 - 8 minute video presentation

  • Coherent communication and clarity of the presentation
  • Relevance of analysis and recommendations to the business case
  • Application of ethical principles relevant to the business case and data utilised
  • Suitability of the final model for the target variable

*Note: Late submission of the assessment task will not be marked and awarded a mark of zero.

Minimum requirements

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

Required texts

There is no prescribed textbook required.


Resources from various sources will be used throughout the course.