Module Name: Data Mining and Business Intelligence

Coursework Title: Application of Data Mining and Business Intelligence to Real Data

Task Details/Description: This assignment focuses on using data mining and text mining algorithms to develop a model to solve a typical business problem in a real case study. In this coursework you are working with the dataset contains information about Road Safety in UK. These files provide detailed road safety data about the circumstances of personal injury road accidents in Great Britain from 1979, the types (including Make and Model) of vehicles involved and the consequential casualties. The statistics relate only to personal injury accidents on public roads that are reported to the police, and subsequently recorded. For further details about this data please see: https://data.gov.uk/dataset/road-accidents-safety-data/resource/6d253c0f-caa4- 4eafaa85-464dc48252da. The dataset Accident, Vehicle and Casualty data can be download from http://data.dft.gov.uk/road-accidents-safety-data/RoadSafetyData_2015.zip

Your tasks:

1. Identify a specific problem related to the road safety that can be addressed using the data mining / text mining methods (10%).

2. Use data mining methods presented in the class, visualize the data and prepare a report on descriptive analysis (10%).

3. Check the quality of the data and prepare a data quality report on the field you will be using for your models. (10%)

4. Use appropriate data mining methods to solve the problem, analyse the results and decide whether they are useful for making a business decision and if so what decision or type of decision would you propose. You will need to use various data mining / text mining methods in the IBM Modeler software. (20%)

5. Using the data sources mentioned in the class for unstructured data, collect related data to the selected topic, use text mining algorithms or web analytics to summaries your findings.

Module Learning Outcomes Assessed:

1. To provide students with an understanding of the data and resources available on the web of relevance to business intelligence.

2. To present the leading data mining methods and their applications to real-world problems;

3. To provide both the practical experience and the theoretical insight needed to reveal patterns and valuable information hidden in large data sets

4. To enable the student to understand various algorithms of data mining so s/he can develop their own learning in the area beyond the topics covered by the course.

5. The student should be able to use Data Mining packages to carry out Data Mining applications