You are required to analyse a large data set of your choice, which has been agreed with your module tutor:

Your project may use any combination of data analysis techniques, data-mining algorithms and software that has been covered in the module.  You may also apply them to any aspect(s) of the dataset for knowledge discovery.  

You should cover the areas indicated below and your findings should be presented in the form of a report.  You will also be expected to give an oral presentation to these mangers.  

Please see the below the aspects that you should consider:

Part A

1. Data Audit and Preparation of Data

1.1. Describe your data (give an overview summary of your data set)

1.2. Select a suitable set of data (will you use a subsets of the data or the entire datasets)

1.3. Identify your input and class variables (which variable are you going to use as your class variable)

1.4. Analyse your variables (for each variable, you need to discuss the variable type, calculate relevant summary statistics and visually display the data)

1.5. Discuss any anomalies in the data (for each variable you need to discuss missing values, outliers etc.)

1.6. Discuss and carry out the appropriate handling of any anomalies identified in section 1.5

1.7. Carry out appropriate pre-processing/transformations of the data set

2. Professional, Legal and Ethical; issues. 

2.1. A discussion of the professional, legal, social and ethical issues related to the analysis of data.

Part B

3. Data Analysis and Visualisation

3.1. Initial analysis the data using visualisation techniques within Tableau (use diagrams/graphs to highlight important patterns/findings)

3.2. Discussion and interpretation of result

4. Data Mining

4.1. Further analysis using Data Mining Algorithms.  Each student is expected to concentrate on one (or possibly two) algorithms.

4.2. Discussion and interpretation of result

5. Conclusion

5.1. A discussion of the overall results (e.g. What were the important findings?)

5.2. A discussion of the data mining results from data mining (How well did the model fit your data?)

5.3. A discussion of the business intelligence that can be obtained from these results.

Data Link