MIT634 Data Visualisation
MIT634 Data Visualisation
- May 12, 2022
- Posted by: Nigel Finch
Unit outline
| Important Update: | Our aim is to provide you with an optimal learning experience, regardless of how this unit is delivered. Teaching will be delivered in line with the most current COVID Safe health guidelines. This may include a mix of online and face-to-face. Please check the learning management system for announcements and updates. Thank you for your flexibility and commitment to studying with Sydney Institute of Higher Education. |
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| Enrolment modes: | Year 2, Semester 2 |
| Credit point(s): | 12.5 |
| EFTSL value: | 0.125 |
| Prerequisite: | MIT631 Data Analytics, MIT632 Data Mining |
| Typical study commitment: | Students will on average spend 10 hours per week over the teaching period undertaking the teaching, learning and assessment activities for this unit. |
| Scheduled learning activities: | 4 timetabled hours per week, 6 personal study hours per week |
| Other resource requirements: | Students will need access to lab computers or will need their own laptops in order to carry out lab exercises and assignments. Students will need to use Microsoft Excel and Tableau. |
Unit description
This unit covers the core data visualisation techniques and technologies to support decision-making processes. Data visualization is the presentation of data in a graphical format for decision makers to easily identify underlying patterns, hence enabling organisations to contexualise data and extract meaningful patterns and trends effectively. This unit provides students with essential information and skills in presenting and analysing data in graphical format. It also enables students to understand different challenges associated with the visualisation and interpretation of big data.
Unit learning outcomes (ULO)
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On the successful completion of this units student will be able to: |
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| ULO1 | Explain principles of data visualisation applicable to current and emerging applications. |
| ULO2 | Evaluate various data visualisation solutions to present data visually. |
| ULO3 | Examine and employ a variety of data visualisation techniques. |
| ULO4 | Demonstrate an understanding of the data visualisation principles and techniques. |
| ULO5 | Create visualisations of data using software tools based on real world datasets. |
Topics to be included in the unit
| 1. | Introduction to data visualisation |
| 2. | From Data to Visualisation: Mapping data onto aesthetics |
| 3. | Coordinate systems and axes |
| 4. | Colour scales |
| 5. | Directory of visualisations |
| 6. | Visualising amounts and Distributions |
| 7. | Visualising Proportions and Associations among two or more quantitative variables |
| 8. | Visualising Time Series and Trends |
| 9. | Handling Overlapping Points |
| 10. | Common Pitfalls of Colour Use |
| 11. | Balancing the Data and the Context |
| 12. | Choosing the Right visualisation Software & Revision |
Assessment
| Assessment Description | Grading and weighting (% total mark for unit) |
Indicative due week |
| Assessment 1: Class Participation | 10% | 12 |
| Assessment 2: Group Report | 30% | 8 |
| Assessment 3: Individual Design Project | 30% | 10 |
| Assessment 4: Individual Practical Project | 30% | 12 |
The assessment due weeks provided may change. Your lecturer will clarify the exact assessment requirements, including the due date, at the start of the teaching period.