Reference no: EM132768666

COM719 Data Analytics - Solent University

Presentation of Data Analysis activities

Assessment for this module consists of a time constrained assignment and a presentation. The time constrained assignment is designed to test the student knowledge of digital data analytics, through which students are expected to critically analyse and answer a combination of multiple choice and true/false questions. This will happen at the end of the module.

The presentation should capture the data patterns and trends applied to a certain case study selected by you the student. As part of the assessment strategy of this module, you should demonstrate a competency in applying data analytics techniques to certain business context, where an online business case study will be selected, an account needs to be created and a successful implementation of what the process of web data analytics entail should be evidenced. This activity will be discussed in group context, where student gets a real world hand on experience in working collaboratively with groups. Through engagement with the formative group-based development work, students should have contributed to and be able to access a group case study containing detailed research, evidence of planning, models and actionable data, testing data and a fully detailed report. They will also have had ample opportunity to have received feedback on this and will have seen the work of other groups.

Formal assessment on this module requires each group to perform a presentation using their collected data, where they showcase their how the collected data will improve the business and potentially will contribute to create an online business strategy. This presentation should be delivered as if it were a pitch to a client. Each member of the team is expected to contribute to the presentation equally and will be assessed on their individual contribution. In addition to this each student should submit a copy of the presentation in which they provide a detailed assessment of their contribution. In doing so they should, justify key analytical decisions, with reference to theory and relevant secondary literature, provide an assessment of the strengths and weaknesses of the collected data and how data analysis will inform more effective business strategy.

Assessment Aim
The presentation should capture the data patterns and trends applied to a certain case study as agreed and selected by you the students. As part of the assessment strategy of this module, you should demonstrate a competency in applying data analytics techniques to certain business/ social/ environmental context.

This activity will be discussed in a group context, where you will get experience in working collaboratively within a group. Through engagement with the formative group-based development work, students should have contributed to and be able to access a question containing detailed research, evidence of planning, models and actionable data, testing data and fully detailed notes. They will also have had ample opportunity to have received feedback on this and will have seen the work of other groups.

Assessment Task Divide in groups of 2/3 members.

Within your group develop a research question:

Through analysis of demographic data of the UK you have to in your group come up with a research question.
For one example I would suggest looking at population health, wealth and well being.
Analysis could look historically at data in terms of population distribution by health and education and also look at projected data in terms of population growth.

This type of analysis is very useful for governments to help plan where resources are to be sourced
The assessment consists of a group project to conduct data analysis on a chosen domain with potential social impact (environment, homelessness, internationalisation). Brainstorming, research, separation of concerns, rational design, software development, retrieval, data mining and analysis and reports are performed by the groups. The projects end with a presentation by the groups to the class.

Action
Discuss what type of domain you wish to choose - do you have a research question?
So one overall aim with up to 5 objectives on how you will achieve that aim - use a mindmap to discuss
What data will be needed?
Where will the data come from? - List what data is required, references
What differing analysis techniques can be used - what are you going to do with the data?
Consider reports that can be produced
How will you share the duties? - this is a group presentation, ensure things are shared equitably, use a Trello Board
The time limit for the presentation is 10 minutes per person.
It is normal to base your arguments on the accepted theories and practices of the day. Failure to acknowledge the work of others within your report represents plagiarism. Evidence of plagiarism will be investigated the University, and disciplinary action may be taken against those concerned.
PowerPoint Slide Format:
The presentation marks will be awarded proportionally for logical structure and presentation style, as well as relevant content. It is suggested that you prepare a script before attempting to do the audio commentary. References should be shown as footnotes on the individual slides.

Activities should demonstrate analysis of a variety of types but should include:
- Looking at time series analysis, include moving averages
- Looking for relationships - correlation, best fit of line, causal relationships
- Comparing sets of data - rebasing
- Where is the data distributed and cleansing the data - Box ‘n whisker example
- Indices and Adjusting for another data set - eg adjusting for inflation

The structure of your presentation could consider the following and provide examples in each:
• What is your research question?
• Where did you get the data?
• What did you have to do to the data to clean and analyse?
• Descriptive analytics - WHAT has happened?
• Diagnostic analytics - WHY has something happened?
• Predictive analytics - WHAT is going to happen?
• Prescriptive analytics - WHAT should be done?
• What is your overall conclusion?

Attachment:- Data Analytics.rar