Apply state of the art business intelligence, data preparation and data mining techniques to a specific case study and dataset. Starting with a business objective and data, work through all stages of an appropriate methodology to extract knowledge from the data in accordance with the business objectives, and present the results to stakeholders in the appropriate language, highlighting how the knowledge learned can be used to add value to the business.
Learning outcomes
Having successfully completed this module, the student will be able to:
- Research appropriate data science / data analytics techniques for a specific problem domain.
- Select from, and apply, a range of advanced, state of the art, data analysis, data visualisation and data mining techniques to a practical case study.
- Understand and interpret a business objective, and translate the business objective into data analytics / data science objective(s).
- Identify possible risks and limitations of a data set in achieving a business objective(s).
- Apply the appropriate analysis techniques to match a business objective.
- Present results to stakeholders in terms of the business objective(s) set, and how the information learned can be used to add value to the business.
Indicative module assessment
The module will be evaluated based on a single project running for the duration of the module. The project will be presented as a case study with the initial business objective(s) and data. Students can base their work on an appropriate, work related project, or on a case study provided by the course tutor. The project will follow a recognised methodology such as CRISP-DM, covering all topics on the syllabus. It will be an individual piece of work submitted by each student.
The deliverables will include:
1. An interim presentation on project progress and outstanding issues.
2. Contributions to peer evaluation on the interim report in the form of constructive evaluation, suggestions and advice.
3. A final report to stakeholders on the results on the project with respect to the business objectives, and how the information learned can be used to benefit the business.
4. A publishable paper justifying the methodology used and presenting the results achieved.