Reference no: EM133116777

Data Visualisation and Dashboarding - University of Westminster

Data Analysis, visualisation narrative and presentation

Learning Outcome 1: discuss and critically apply the basic principles to data visualisation techniques;

Learning Outcome 2: select and justify appropriate tools for data visualisation and Dashboarding;

Learning Outcome 3: evaluate critically data visualisation using appropriate software tools;

Learning Outcome 4: use a design process to build interactive Dashboards;

Learning Outcome 5: synthesise the application of raw data into meaningful visualisation results and justify the appropriate techniques.

Coursework Description

1. Formulate a research question - this will frame your analysis.

2. Carry out exploratory data analysis of the data using R or Tableau or both. You should visually explore the data as part of your data analysis.

3. Using the findings from your analysis, construct a data graphics narrative to inform the viewer of the results of your data analysis and how you have interpreted them.

4. Refine the data visualisations produced so you can use them in a short presentation of the data story. Use feedback to improve your graphics.

5. Write a short report explaining your process and critical thinking.

6. Present your data story using Panopto and submit a link to your presentation.

Report

Write a report detailing your work. The report must not be longer than 4000 words (excluding cover sheets, appendices, data tables). You must include at least five different visualisations but should use as many as are needed to support your findings.

The report must cover the following areas:

• Research Question: A research question is a clear and concise question summarising the issue your research will investigate. It should reflect something about you being genuinely curious.

• Data Acquisition: State the source of the data you are using (who compiled the data and where it can be downloaded). Provide a short description of the data set(s). Consider who compiled the data and its implications on the analysis (e.g. how reliable can we expect it to be, does it cover all areas you are interested in, and so forth).

• Preparation: State what steps you took to prepare the data. What checks did you carry out to ensure the data is in acceptable shape. State if you needed to mutate the data and what tools you used.

• Exploratory Data Analysis: Present and evaluate the findings of your data analysis. This section needs to answer your research question and should contain most of your charts. Critically evaluate and reflect on the methods you used. Which strategies were the most effective, and which ones were the least effective? Why?

• Visualisations: State which visual encodings you considered and which encodings you chose. Justify your decisions. Reference to published works on these topics would be appropriate here. You also need to discuss how you improved your data visualisations using feedback from someone who has not seen your graphics before.

Presentation
You need to present the findings of your analysis and answer the research question in a short presentation. You should use the visualisations created earlier. Show a clear narrative and answer the research question. You do not need to reflect on the methodology of your data analysis or on the process of creating your graphics.

The presentation must not be longer than 5 minutes; any content after 5 minutes will not be used to mark the presentation.

You need to record the presentation with Panopto and submit the link to the recording. You must also submit a PowerPoint or a PDF file of the presentation. Note: if you're using Tableau stories for your presentation, you must export it as a PowerPoint file and submit this file.

Attachment:- Data Visualisation and Dashboarding.rar