Marketing

UNIT DESCRIPTION

In this unit, students will acquire the skills and techniques required to analyse, manage and mine data. They will focus on the interpretation and reporting of results and recommendations in a business environment. Students will expand their knowledge of qualitative techniques including an introduction to data mining - the process of building mathematical models that explain and generate hidden knowledge from datasets that facilitates the exploration and extrapolation of data for the benefit of a business. The techniques will be tested and expanded through the use of case studies that are presented and analysed with students experiencing the issues and limitations of analysis with what may appear in the first instance to be a straight forward situation.

LEARNING OUTCOMES

On successful completion of this unit students will be able to:

1. Articulate the main challenges and potential solutions in representing and sharing business knowledge.
2. Design data mining and relationship models to support and provide business solutions
3. Make decisions and recommendations based on analysis of data and to communicate these findings to stakeholders in a professional and persuasive manner.

CERTIFICATION

The optional assessment tasks associated with this unit provide an opportunity for participants to consolidate their learning and to benchmark their understanding against the standard set by Chancellor Institute. Participants enrolled in this unit who successfully complete the optional assessments will qualify for a grade, academic transcript and certificate of completion for that unit. For further details about the assessments, please click on the Curriculum tab or contact our course advisors. Additional unit fees apply for students electing to undertake assessments. Participants who elect not to complete the optional assessments for this unit will receive a certificate of participation for the unit.   Shareable on Linkedin. You can share your certificates in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.