Issued: Monday of Week 4
Due: 11:59PM (local Time) Wednesday of Week 7 Weight: 60%
Report Length: 1500 – 4000 words + Tableau *.twbx file
Overview
During this assessment you will produce an interactive Tableau Dashboard and an accompanying report detailing the planning of the Tableau Dashboard.
Background
Tableau dashboards are used extensively for data communication and careful design of a dashboard is essential to deliver the dashboard purposes. An effective plan incorporates planning at two levels, the individual visual (worksheet) level and the dashboard level.
Planning for both the visualisation (worksheet) and dashboard levels can be done using the four-stage planning cycle of (1) Domain situation (2) Data/Task abstraction (3) Visual Encoding and (4) Algorithm selection. Planning the worksheets and dashboards is an iterative cycle as the themes of the visualisation choices needs to be coherent to effectively communicate the desired messages. Additionally, the interactivity between visualisations, and between the dashboard and the visualisations, also needs to be coherent, cognitively easy (intuitive) and focused to aid users draw meanings from the data.
Learning outcomes
- Demonstrate sound knowledge of the basic theory, principles and concepts that underpin data visualisation techniques and strategies.
- Apply related Visualisation principles and approaches to analyse, evaluate and improve visualisation.
- Plan and communicate interactive visualisations using a formal planning process
- Application of the Tableau visualisation software.
Data
For this assignment, you are to produce a Tableau dashboard using the supplied NAPLAN or AirBNB data sets, which is located and described in the Data Sets folder of this assessment. The data sets comprise of multiple data files, any combination of which can be used in your dashboard.
Assessment Tasks
This assessment comprises of two tasks:
- A dashboard visualisation plan
- A Tableau dashboard implementing the plan. The Tableau Dashboard must contain a Map worksheet plus a
minimum of three other worksheets containing charts (visualisations).
The dashboard purpose must relate to the chosen data set, otherwise you have the liberty to choose the dashboard purposes.
IMPORTANT
Your submitted Tableau dashboard MUST be a .twbx file. This is format will save the data, and any changes you have made to the data, in the dashboard file.
A. Dashboard Visualisation Plan: The report
The plan may deviate from the final produced Tableau dashboard. However, the dashboard must be a broad implementation of the proposed plan. You are required to write the plan for university academics or other data scientists (i.e. NOT for target audience of the intended dashboard). Suggested word lengths are provided in parenthesis (brackets).
Dashboard Plan Sections:
- Dashboard Purpose. The dashboard purpose must include: (300 – 500)
- Identification of the target audience (domain) and provide a general description of that audience
- Visualisation, Data and Time assumptions concerning the target audience
- The intent(s) of the dashboard
- Dashboard Layout. Describe (and/or provide wireframe), discuss and justify the layout of the dashboard including (100 – 600)
- Worksheets (including the geographic map)
- Filters
- Annotations
- Navigation elements
- Highlights
- Parameters
- Dashboard Visualisation Themes: Describe and justify the Marker, Channel and Aesthetics themes used for the dashboard and across worksheets (100 – 400)
- Worksheets. For each Worksheet, including the geographic map, detail/tabulate: (800 – 1500)
- Identification of
- Intent
- Visualisation type and
- Task abstractions of the worksheet
- Discussion of alignment between the:
- Worksheet intent and the dashboard intent/desired response
- Worksheet Visualisation type and the Audience assumptions
- Worksheet task abstractions (including any interactivity) and the worksheet and dashboard intent/desired response
- Identification of
- Dashboard Data – this section is to be a table(s) comprising of: (100 – 300)
- Identification and summarisation of all required original variables
- Identification, description and summarisation of any calculated parameters or variables derived from the original variables
- Identification of where the variables/derived values are used in the dashboard (i.e. worksheet number, visualisation, annotation, filter number, highlight., tooltip, etc)
- Dashboard Interactivity. (100 – 400)
- List or tabulate the dashboard interactivity elements including any:
- Filters
- Highlights
- Action filters
- Navigation buttons
- Annotations
- Tooltips
- Discuss the alignment of these interactive elements with the
- Audience assumptions
- Dashboard Intent/Desired response
- List or tabulate the dashboard interactivity elements including any:
- Major implementation deviations. Tabulate all major deviations from the plan to the final Tableau dashboard. (100 – 400)
Discussions and justifications need to be linked to visualisation principles or theory.
B. Tableau Dashboard
You must use one of the provided datasets and use Tableau to implement the project in Assessment 4. You are to implement an interactive Tableau dashboard that uses at least four (4) Tableau worksheets that contain charts (visualisation) – and one of the worksheets must be an interactive geographic map. The interactive map must interact with at least one other Tableau worksheet contain a chart (visualisation). For example, selecting a data marker on the map filters the data presented on a bar chart.
The maximum size of the dashboard is 1000 by 800 pixels, the default desktop browser size.
The dashboard is an implementation of the visualisation plan and the dashboard need to demonstrate the following:
- Interactivity. You should demonstrate use Tableau interactive elements in both the tableau dashboard and your tableau worksheets. Tableau interactivity elements include:
- Filters
- Highlighting
- Action filters
- Annotations
- Tooltips
- Data Drill Down/Up
- Paging or Cascading techniques. i.e., interactivity between worksheets
- Visualise and calculate complex data. Demonstrate visualisation of complex data in at least two worksheets and on the dashboard panel. Complex data is data that is not immediately available from the raw data sources. For example, you may create calculated fields, parameters or analytics to derive information, new variables, annotations, frequencies, trend lines, or clusters. You should demonstrate:
- Calculation of new fields and parameters
- Use of Tableau analytics
- Application of complex data in worksheets using a variety of visualisation types (charts)
- Integration of calculated fields/parameters with filter, chart, marker, channel or annotation controls
- Application of design principles. Effective use of markers, channels, charts, controls and effective use of layout (space), both on a worksheet and dashboard level. You should demonstrate
- Effective use of dashboard space. You may use all four worksheets on the dashboard panel – or alternatively one (or more) worksheets can be used within tooltips in the dashboard.
- Coherent use of a visualisation theme (i.e., channels and marker choices) on a dashboard and worksheet levels
- Application of visualisation choices for expressiveness and effectiveness
- Application of visualisation principles for aesthetics
Assessment submission:
Include the following in your submission
- The task cover sheet
- A PDF document of the dashboard plan
- A Tableau Desktop *.twbx file containing all worksheets, data, derived data, and the dashboard.
Use the following method to name your assessment PDF: YourLastName_YourFirstName_MA5830_A4.pdf
Use the following method to name your assessment Tableau twbx file: YourLastName_YourFirstName_MA5830_A4.twbx
Upload all submission files in one go. You can upload as many times as you want, but only the last submission is graded.
Criteria Exceeds/Sophisticated Expectations (75-100%) Meets/Above Expectations (50-74%) Unsatisfactory / Below Expectations (0-49%) Dashboard purpose 5% of total grade Identifies, discusses and prioritises all key dashboard purposes: Domain and assumptionsIntent(s) and desired response(s),Task abstraction(s) Identifies and discusses all key dashboard purposes: Domain and assumptionsIntent(s) and desired response(s),Task abstraction(s) Partially identifies and/or explains some key issues in a superficial data science related situation in a complex data science related situation, drawing upon relevant theory from a wide range of credible sources; eliciting insightful knowledge linking to broader relationships and, bring in originality of perspective in a routine data science related situation, drawing upon relevant theory Worksheet alignment 10% of total grade Identification, prioritisation plus discussion of the alignment of all key Worksheet issues with Dashboard/Worksheet purposes: Intent,Visualisation (chart) typeTask(s) abstraction(s) in a complex data science related situation, drawing upon relevant theory from a wide range of credible sources; eliciting insightful knowledge linking a variety of visualisation types and intents to broader relationships and, bring in originality of perspective Identification and discussion of the alignment of all key Worksheet issues with Dashboard/Worksheet purposes: Intent,Visualisation (chart) typeTask(s) abstraction(s) in a routine data science related situation, drawing upon relevant theory Partially identifies and/or explains some key issues in a superficial data science related situation Data 5% of total grade Identification and usage of key data including: Summarisation of all required dataDetail and summary of derived valuesUsage of required data in a complex data science related situation; discussion of data limitations and derivation of new data information eliciting insightful knowledge linking visualisation intents to broader relationships and, bring in originality of perspective Identification and usage of key data including: Summarisation of all required dataDetail and summaries of derived valuesUsage of required data in a routine data science related situation, drawing upon relevant theory Partially identifies and/or explains some key issues in a superficial data science related situation Marking Criteria and Rubric: MA5830 Assessment 4 Visualisation Plan (45 % of total grade)
Criteria | Exceeds/Sophisticated Expectations (75-100%) | Meets/Above Expectations (50-74%) | Unsatisfactory / Below Expectations (0-49%) |
Interactivity 15% of total grade | Identifies and discusses, in the context of the dashboard purposes, all key interactivity elements: Map filteringMap NavigationFiltersAction filtersHighlightsTooltips in a complex data science related situation. Interactive elements are used to elicit insightful knowledge linking to broader relationships and, bring in originality of perspective | Identifies and discusses, in the context of the dashboard purposes, all key interactivity elements in a routine data science related situation, drawing upon relevant theory. | Partially identifies and/or explains some key issues in a superficial data science related situation |
Visualisations and Aesthetics 10% of total grade | Identify, discuss and justify all key elements of the Dashboard layoutWorksheet layoutDashboard marker/channel/aesthetics themes elements in a complex data science related situation. Visualisation elements are used to elicit insightful knowledge linking to broader relationships and, bring in originality of perspective | Identify and discuss all key elements of the: Dashboard layoutDashboard marker/channel/aesthetics themes elements in a routine data science related situation, drawing upon relevant theory. | Partially identifies and/or explains some key issues in a superficial data science related situation |
Rubric continued next page
Tableau Dashboard (55% of total grade)
Criteria | Exceeds/Sophisticated Expectations (75-100%) | Meets/Above Expectations (50-74%) | Unsatisfactory / Below Expectations (0-49%) |
Map 10% of total grade | Customised use of Tableau map controls for: Geo-encodingNavigationHighlightingFiltering cascading to other worksheetsParameter/field calculation integration with map controlsMap integration with parameter/field/marker/channel control integration Tableau used in a complex data science related situation. Visualisation elements are used to elicit insightful knowledge linking to broader relationships and, bring in originality of perspective. High degree of customisation used along with minimal use of standard Tableau defaults. | Appropriate or default use of Tableau map controls for: Geo-encodingNavigationFiltering cascading to other worksheets Tableau used a routine data science related situation. Some customisation applied along with standard Tableau defaults. | Partial implementation in Tableau with some key features not present or superficially attempted. Predominately implemented using Tableau defaults only. |
Interactivity (excluding map) 15% of total grade | Customised use of Tableau interactivity controls for: Filters including resettingAction filtersAnnotationsHighlightingTooltipsData Drill Down/UpCascading techniquesNavigationWorksheets interact dynamicallyInteractive elements interact dynamically with other interactive components or other visual elements (such as layout) | Appropriate or default use of Tableau for: FiltersAction filtersAnnotationsTooltipsData Drill Down/UpCascading techniquesNavigation | Partial implementation in Tableau with some key features not present or superficially attempted. Predominately implemented using Tableau defaults only. |
Tableau used a routine data science related situation. Some customisation applied along with standard Tableau defaults. | |||
Tableau used in a complex data science related situation. Interaction elements are used to elicit insightful knowledge linking to broader relationships and, bring in originality of perspective. High degree of customisation used along with minimal use of standard Tableau defaults |
Criteria | Exceeds/Sophisticated Expectations (75-100%) | Meets/Above Expectations (50-74%) | Unsatisfactory / Below Expectations (0-49%) |
Visualise and calculate complex data. 10% of total grade | Customised use of Tableau visual controls for: Calculation of new fields and parametersUse of Tableau analyticsApplication of complex data in worksheets using a variety of visualisation types (charts)Integration of calculated fields/parameters with filters, chart, marker, channel or annotation controls Tableau used in a complex data science related situation. Derived data elements are integrated into other Tableau controls and visualisations used to elicit insightful knowledge linking to broader relationships and, bring in originality of perspective | Appropriate or default use of Tableau for: Calculation of new fields and parametersUse of Tableau analyticsApplication of complex data in worksheets using a variety of visualisation types (charts) Tableau used a routine data science related situation. Some customisation applied along with standard Tableau defaults. | Partial implementation in Tableau with some key features not present or superficially attempted. Predominately implemented using Tableau defaults only. |
Application of design principles. 20% of total grade | Customised use of Tableau visual controls for: Innovative and effective use of dashboard spaces.Novel and coherent Channels and Marker choicesHighly relevant application of visualisation choices for expressiveness and effectivenessConsistent application of visualisation principles for aesthetics Tableau used in a complex data science related situation. Design principles routinely used to highly customised Tableau controls and contain cross-linkages to interactivity and derived data. Designs are integrated into other Tableau controls and visualisations used to elicit insightful knowledge linking to broader relationships and, bring in originality of perspective. High degree of customisation used along with minimal use of standard Tableau defaults | Appropriate or default use of Tableau for Effective use of dashboard spaces.Coherent Channels and Marker choicesApplication of visualisation choices for expressiveness and effectivenessApplication of visualisation principles for aesthetics Tableau used a routine data science related situation. Some customisation applied along with standard Tableau defaults. | Partial implementation in Tableau with some key features not present or superficially attempted. Predominately implemented using Tableau defaults only. |
Sophisticated
Performance far exceeded expectations due to exceptionally high quality and novelty of work in all essential areas, resulting in an overall quality of work that is sophisticated. This rating is achievable by any student though given infrequently.
Exceeds Expectations
Performance consistently exceeded expectations in all essential areas and the quality of work overall is excellent.
Above Expectations
Performance consistently met expectations in all essential areas and at times possibly exceeding expectations, and the quality of work overall is very good
Meets Expectations
Performance consistently met expectations in all essential areas and the quality of work overall is satisfactory
Below Expectations
Performance did not consistently meet expectations – performance failed to meet expectations in one or more essential areas and/or one or more of the most critical goals were not met.
Unsatisfactory
Performance was consistently below expectations in most essential areas of responsibility, and/or critical goals was not made. Significant improvement is needed in one or more important areas.
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