This assignment involves the analysis of one of the UK\'s largest collections of UK and international social, economic and population data provided by government departments and agencies, public bodies, and local authorities

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Coursework Assignment

The coursework is an individual assessment weighted 50% of the marks for the module. It is primarily an exercise in applying data mining knowledge and techniques to a practical problem. This assignment involves the analysis of one of the UK's largest collections of UK and international social, economic and population data provided by government departments and agencies, public bodies, and local authorities. You are asked to mine the data to help tackle key challenges which many communities face in UK such as the skills gap, poverty and inequality, discrimination, homelessness, crime, pollution, and health and well-being. You need to provide appropriate documentation detailing the stages of the CRISP-DM method and a critical evaluation of possible benefits and commercial risks of the project.

Coursework Submission  

The final report of your mining project is due on 14th May 2021. All your work must be documented into a single PDF file. It should have a cover page with module code and title, your data mining project title, student ID and name. The document must be submitted via WebLearn.

Please note that plagiarism is a serious academic offense, for which penalties are severe. All suspected cases of plagiarism will be reported.

Detailed Specifications 

The dataset used for the coursework is based on real-world data sets provided by data published by government departments and agencies, public bodies, and local authorities, You are asked to use SAS Enterprise Miner to mine the data to discover some interesting patterns of UK to help tackle key challenges which many communities face in UK such as the skills gap, poverty, and inequality, discrimination, homelessness, crime, pollution, and health and well-being.

Your project proposal with chosen mining topics and data sets will be peer-reviewed and have to be approved by the module leader by week 4 via Discussions on the module web learn.

The final report should include details of the following stages of the CRISP-DM method and a critical evaluation of possible benefits and commercial risks of the project.

·   Business and data understanding

·   Data preparation and exploration

·   Modelling

·   Evaluation and results explanation

·   Plan for deployment 

 

·   Evaluation of possible benefits and commercial risks

Attachments:

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