Practical data analysis

Section 1 Module Specific Assessment Brief

 

 

Coursework Brief

 

Total Marks:     100 (100% weighting)

Word count:      The overall word count is 3000 words.

 

All submissions must have a completed cover sheet (see Appendix B) attached to your submission.

 

Summative Assessment Brief

 

This is an individual assignment.  You are required to create a data architecture for a big data application that would be relevant to your organisation or to an organisation like your own.  You are also required to generate a relevant data set, carry out an analysis, and finally discuss data governance.

Since you will be using synthetic data rather than real data, we can think of this assignment as developing a proof of concept to demonstrate the power of data analytics to stakeholders.

There are four main tasks specified on the next pages.

 

 

 

 

 

 

 

 

 

 

 

 

Task 1: Data Architecture Analysis (25 Marks)

            (Write in third person  – academic style)

 

The set text provides an end state architecture to which organisations should aspire. It is shown below.

 

 

Snapshot : from: Inmon, W. and Linstedt, D. (2019) Data Architecture: A Primer for the Data Scientist, Academic Press; 2nd edition, pp 48

 

 

Devise a big-data-oriented application relevant to your organisation (or organisation like your own) and consider how that application could be represented using the given architecture as a foundation.

Provide a description of the application, stating the main data components, their sources and their relationships. Justify the data components included.

Amend the diagram given above to include the data components of your application.

Explain how big data techniques might be used to harness and process the data within your application.

 

Task 2: Data Analysis (40 marks)

            (Write in third person – academic style)

You will carry out a data analysis and produce visualisations. You will need a data set which can be analysed.  You will also need a research question.

• Research question and hypotheses (10 marks)

Identify a research question that might be usefully answered using your analytics record. Develop hypotheses.

Evaluate the potential impact of insights that might occur following exploration of the research question.

 

• Dataset Generation (10 marks)

Identify data from your application that might be analysed to provide business insights and in particular to answer your research question in (a) above. Based on your selection, create a data set with at least 1000 rows. You can create the data set either using real data (suitably anonymised) or, if this is not possible, you will need to generate a realistic data set. You will need to specify realistic shape and relationships within the data in order to generate realistic data. If you use real data make sure you have permission from your organisation and that your use complies with your organisation’s data governance policy.

Briefly explain why the data chosen has been selected and the reasoning behind your design of the data shape and relationships. The data set will form your analytics record.

Include an appendix that describes the meta-data of your data set together with a sample of some rows.

 

• Hypothesis Testing (10 marks)

Analyse the data against the hypothesis.

Carry out suitable statistical significance testing.

Evaluate results and justify statistical significance testing method selected.

 

• Analysis and Visualisation (10 marks)

Using Power BI or another suitable visualisation tool, create at least three visualisations from your data set. Provide a discussion of the visualisations selected, explaining how they were created and what additional insight they bring.

 

Task 3: Data Governance (15 marks)

            (Write in third person – academic style)

 

Outline a data governance framework suitable for the organisation. Justify the components included and outline the responsibilities of the data governance function.

 

Task 4: Evaluation (10 marks)

            (Write in first person – reflective style)

 

Evaluate your experience in carrying out the assignment. What went well and what was your response to any challenges? Briefly discuss your main points of learning.

 

 

Academic Conventions (10 marks)

The standard of academic writing will be considered as well as the report presentation and structure.  Roehampton Harvard (https://library.roehampton.ac.uk/ld.php?content_id=32542499) referencing style is expected.  Sections should be numbered.  Figures and tables should be numbered and should have captions. Pages should be numbered.  Appropriate front pages should be used.

 

 

Marking Rubric for Coursework

 

Appendix A Marking Rubric for Coursework

Criteria	80-100%	70-79%	60-69%	50-59%	40-49%	0-39%
Data Architecture Analysis         (25 marks)	Analysis of architecture is exceptionally insightful and accurate with strong academic foundation and contextualisation. All requirements addressed.     20 to 25 marks	Analysis of architecture is accurate and excellent insight is provided with solid academic foundation and contextualisation. All requirements addressed.   18 to 19 marks	Description of the application is clear.  Analysis of architecture is very good. There is at least one area of improvement.     15 to 17 marks	Description of the application is mostly clear.  Analysis of architecture is good. There are at least two areas of improvement.     13 -14 marks	Description of the application is adequate.  Analysis of architecture is adequate. There are many areas of improvements.       10  to 12 marks	Insufficient relevant content.             0 to 9 marks
Data Analysis         (40 marks)	Exceptional insight, analysis, and accuracy across all aspects of the task as stated in the brief.     32 to 40 marks	Excellent insight, analysis, and accuracy across all aspects of the task as stated in the brief.     28 to 31 marks	Very good analysis and outcomes regarding developing dataset, performing analysis and creating visualisations.   24 to 27 marks	Generally good analysis and outcomes regarding developing dataset, performing analysis and creating visualisations.   20 to 23 marks	The task components are completed generally to a satisfactory standard.       16 to 19 marks	Insufficient relevant content.         0 to 15  marks
Data Governance     (15 marks)	Outstanding discussion of data governance with strong academic foundation and contextualisation.   12 to 15 marks	Excellent discussion of data governance with strong academic foundation and contextualisation.   11 marks	Very good discussion of data governance. There is at least one area of improvement.   9  to 10 marks	Good discussion of data governance. There are at least two areas of improvement.     8 marks	Satisfactory discussion of data governance. There are many areas of improvement.      6 to 7 marks	Insufficient relevant content.         0 to 5 marks
Evaluation   (10 marks)	Exceptional lucidity and depth are evident in your evaluation.     8 to 10 marks	Excellent lucidity and depth are evident in your evaluation.     7 marks	Clear and relevant evaluation is provided.     6 marks	Good evaluation which might have been further developed in places.   5 marks	Satisfactory evaluation but clarity and depth could be developed.     4 marks	Insufficient relevant content.       0 to 3 marks
Academic Conventions   (10 marks)	Outstanding, well-presented report that contains all key elements. Consistently accurate and assured use of academic conventions.   8 to 10 marks	Excellent, well-presented report that contains all key elements. Accurate and assured use of academic conventions     7 marks	Very good, well presented report that contains most of the key elements. Mostly accurate and assured use of academic conventions. 6 marks	Good report that contains most of the key elements. There are some areas of improvement.       5 marks	Basic, some key elements may be missing from the report. Academic conventions used weakly. A number of areas of improvement.   4 marks	Unclear communication. Essential parts missing. Inaccuracies evident. Academic conventions largely ignored.   0 to 3 marks