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FIT5147 Data Exploration and Visualisation
Semester 1, 2025
Programming Exercise 1: Tableau (5%)
1. Instructions & Brief
2. Assessment Resources
3. Assessment Criteria
4. How to Submit
5. Word Count & Penalties
1. Instructions & Brief
Relevant learning outcomes for FIT5147:
THE DATA:
The data set used in this assignment is based on the AusStage online resource. It is “a data set of live Events with dramatic and performance content covering all of Australia and New Zealand plus many additional International links” (AusStage, n.d.) and is regularly updated.
While the data we are using was collected in February 2025, it includes both recent events as well as ones from previous centuries.We introduced this dataset in the Week 1 Workshop. For this assignment, use the provided PE1 dataset to produce your Tableau visualisations and visual analysis. It is based on that found in AusStage but has been slightly modified.
To enhance your understanding of the context and metadata, you can check the data source link. Using the various interactive tools for the data source of the full dataset may help enrich your visual analysis: https://www.ausstage.edu.au/pages/learn/search-ausstage . If you discuss or replicate the visualisations or metadata provided by AusStage, be sure to reference these correctly in your report1 .
Please note that the event and performance names relate to real Australian performance art and culture. Some names may have some explicit terms.
|
Column |
Description |
|
Event Name |
The title or name of an Event. |
|
Event Identifier |
A unique number identifying an Event in AusStage. |
|
First Date Year |
The year of the Event's first public presentation, including previews |
|
First Date |
The year (and day or month if known) of the Event's first public presentation, including previews |
|
Last Date |
The year (and day or month if known) of the Event's final public presentation. |
|
Venue Name |
The name of the Venue where an event happens. |
|
Venue Identifier |
A unique number identifying the Venue where an event happens. |
|
Suburb |
The suburb or local district where the Event happens. |
|
State |
The Australian state or territory where the Event happens. |
|
Country |
The country where the Event happens. |
|
Primary Genre |
The kind of Event, as defined by its main mode of performance. |
|
Organisations |
The name of the organisation/s associated with an Event. |
|
Contributor Count |
Number of contributing people recorded in AusStage for this Event. |
|
Resources Count |
Number of related resources recorded in AusStage for this Event |
|
Longitude |
Geographical Location (longitude) of the Venue |
|
Latitude |
Geographical Location (latitude) of the Venue |
References:
VISUAL ANALYSIS QUESTIONS TO BE ADDRESSED
Using the data and visual analytics, you will need to answer the following questions:
To answer this question, discuss how you are going to identify, measure and visualise what are the most common events.
To answer this question, discuss how you are going to identify, measure and visualise the number of events started each year.
To answer this question, treat each Organisations value as a single organisation, even if it includes different groups. Discuss how you are going to measure and visualise the number of events for each organisation.
1D. How many organisations started events each year over the last 25 years?
To answer this question, discuss how you are going to identify, measure and visualise the number of events started each year.
To answer this question, discuss how you are going to identify, measure and visualise the number of years each event ran in.
For this question, you need to discuss whether your visual analytics for 1A-E have enabled you to answer this question or not. Be sure to explain how you came to that conclusion.
The task has two components: data exploration using Tableau, and a short written report.
Data Exploration using Tableau:
1. Load the dataset in Tableau Public/Desktop
2. Use data visualisation in Tableau to check for and find at least two aforementioned irregularities in the dataset. Each type of irregularity may occur multiple times in the data. These irregularities are not related to missing data.
3. Amend the data to correct these errors using any tool of your choice (e.g., Excel, Python, R, Tableau) and justify your choice of correction based on the irregularity.
4. Use Tableau to create at least one visualisation per question (not more than 2 per question) to conduct your visual analysis and answer the above question. Remember to select appropriate visual variables to suit the data and your chosen visualisation.
5. Polish up your visualisations for presentation, e.g., add a suitable title, correctly label your axis, make sure labels and values are not truncated, include a legend. Ensure the font, font size and colour are suitable and legible for your report.
6. Write a report that presents and describes your data exploration process and visual analysis. See below for details.
This exploration must be submitted as a Tableau workbook file (*twb suffix). Note: Indications of missing data like UNKNOWN/unknown, NULL/null, N/A, tba values should not be regarded as irregularities for this assignment. If Tableau has any issues automatically recognising any date or time information, then this is not to be regarded as an irregularity for Step 2 but can be corrected by you in Tableau.
Once you have finished your data exploration, write a report that contains the following information:
- A brief explanation (maximum of one paragraph per error) and an accompanying image of each of the errors or irregularities that you havefound, showing how you found them using Tableau, and explaining & justifying how you resolved them. The image must show a relevant visualisation, not just the data or a table.
- Explanation of what insights you have found out through the visual analysis in order to answer the questions. This should include:
- Your answer to the question, based on your visualisation(s). Includerelevant visualisations in 1 or 2 figures per question.
- Description of your visualisation(s) and how they relate to the dataand question (i.e. why it is an appropriate visualisation choice)
- Justification of your visualisation(s) and choice of visual variables
- Any further insights, or issues that you have identified from the dataor visualisation(s) while answering the question.
- Be submitted as a PDF file
- Be no more than 5 pages in length, including figures, with a minimum font size of 10 (title page and any table of contents are excluded from the page limit)
- Be properly structured with headings, subheadings, figure captions (in-text referencing of captions), page numbers, and references (where appropriate)
- Have high quality images of your visualisations with clearly readable and legibletext/labels (presume that it is read as part of an A4 document with no zooming).
- You must use proper academic referencing for all reports in this unit. This shouldfollow either the APA or IEEE structure as recommended by the Faculty. Use thelibrary referencing guide for support.
- Not include any code snippets except for key Calculated Fields in Tableau.
- No Generative AI software or system may be used to complete this assessment task. This includes using any software that paraphrases, translates or rewrites your text.
2. Assessment Resources
- AusStage_S12025PE1.csv (Available on Moodle)
3. Assessment Criteria
The following outlines the criteria which you will be assessed against. The focus of the marker will be on what you have included in your report, but your submitted Tableau Workbook may be examined if there are any concerns with the academic integrity of your work.
- Demonstrated ability to check and clean data and read into Tableau [1%]
- Demonstrated ability to appropriately visualise data for data exploration using Tableau [2%]
- Demonstrated ability to see trends/patterns in data [1%]
- Quality of report [1%]
4. How to Submit
1. Save your report as a .pdf file.
2. Name your file using the following structure PE1_Surname_StudentID
3. Save your Tableau workbook as a .twb file.
4. Compress the .twb workbook file into a .zip file so it can be submitted to Moodle. DO NOT include your report in your zip file, only your Tableau workbook.
5. Name your zip file using the following structure PE1_Surname_StudentID
Please note that your assignment MUST show a status of "Submitted for grading" before it can be marked. Any submission left in draft mode will not be marked. We recommend always double checking your submission has been completed and that you have uploaded the correct files. Penalties will apply to any submission which needs amendment after the deadline.
5. Word Count & Late Penalty
1 mark (out of the total of 5) will be deducted if the report does not meet these requirements.
As per Monash policy: All late submissions will receive a penalty of 5% per day (0.25 marks per day out of a total of 5 marks) late inclusive, including weekends. Work submitted more than seven days after the due date will not be marked.