Creating visualisations that can enable you

Reference no: EM133133859 , Length: 10 slides

MIS609 Data Management and Analytics - Torrens University

Assessment- Data Analysis and Visualisation Presentation

Learning Outcome 1: Explore data management techniques and apply when and where applicable.

Learning Outcome 2: Analyse and apply data issues in an organisational context.

Learning Outcome 3: Effectively report and communicate findings to a business audience who are not necessarily IT professionals.

Learning Outcome 4: Critically analyse and interpret data analytics, its principles and tools for organisational problem solving.

Task Summary
In groups, apply data analysis and visualisation skills, and create meaningful data visualisations for secondary data (selected after approval of your facilitator). Then, create a 5-10-minute presentation as a short video collage explaining the findings of your visual analysis.

Context
In Module 3, 4 and 5, you learnt about contemporary Data Management practices, Data Analysis and Data Visualisations. You have also explored what the issues related to data are. This group presentation gives you the opportunity to select data that does not have any ‘issues' and perform analysis on it using a tool, creating visualisations that can enable you to get meaningful insight into what selected data has to offer.

Task Instructions

Step 1: Group formation and registration
Form groups of two members each. Please refer to the attached Group Formation Guidelines document for more information about group formation and registration. You may seek help from your learning facilitator.

Step 2: Select secondary data from the internet. Make sure you select the data after approval of your learning facilitator.

Step 3: Find out the issues that the selected data has. Make note of all the identified issues. For every issue identified you should have a solid rationale.

Step 4: Select a data analysis / visualisation tool. You can surf the web and find out some free data analysis / visualisation tools. Some of the recommended tools are Tableau, Microsoft Excel, Microsoft Power BI, Qlik and Google Data Studio. Make sure that before you select a tool, you carefully understand the merits and demerits of that tool. Also discuss with your facilitator the choice of your tool.

Step 5: Analyse selected data using the selected tool and try creating meaningful visualisations that give you more visual insight into data.

Step 6: Based on analysis using visualisation, identify important finding about that data.

Step 7: Carefully identify your limitations.

Step 8: Now create a Microsoft PowerPoint presentation having the following sections: Section1: Selected Dataset
• Provide a link to data.
• Explain why you select this data.
• Explain the issues in the selected data. Section 2: Selected Analysis/Visualisation Tool
• Explain why you selected this tool.
• What were the problems that you faced with this tool?
• What are the benefits and drawbacks of the selected tool? Section 3: Visualisations (Diagrams)
• On every PowerPoint slide, copy a diagram (visualisation) and beneath every diagram briefly explain what information/knowledge you obtained from the diagram. Make as many PowerPoint slides as you want to.
Section 4: Findings and Limitations
• Explain what your findings are about the selected data as a result of data analysis (/ visualisation) that you have performed.
• Enlist your limitations. Section 5: Group Work Distribution
• Categorically explain how work was distributed between group members.

Step 9: Now using the PowerPoint, create a video collage in which your facilitator should be able to see you as well as the PowerPoint slides in the video. Please note that this 5-10-minute video is like an online presentation. Both members of the group should take part in the video equally. Please ensure that you are objective in your presentation (PowerPoint and video). Plan and rehearse what you have to speak in the video before creating it.

Referencing
It is essential that you use appropriate APA style for citing and referencing research.

Attachment:- Data Management and Analytics.rar

Reference no: EM133133859

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