Business Intelligence MGT5470

  • Academic Session: 2023-24
  • School: Adam Smith Business School
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: No

Short Description

Business Intelligence refers to the technologies, applications, and practices used for the collection, integration, analysis, and presentation of business data, with the purpose of supporting effective decision-making. This course is composed of two main components: data-driven models for supporting business decisions and practical applications of software used for business analytics.

Timetable

The course will be delivered in the form of a series of lectures and workshops in semester 2, 2 x 3 hour lectures and 4 x 3 hour workshops. Utilizing a combination of synchronous and asynchronous learning methods.

Requirements of Entry

Please refer to the current graduate prospectus at http://www.gla.ac.uk/postgraduate/prospectus. 

Excluded Courses

MGT5372 Data Science for Marketing Analytics

Co-requisites

None

Assessment

Intended Learning Outcomes

Course Aims

The aim of this course is to equip students with strong foundational knowledge of basic analytics concepts, models, skills, and tools to support decision-making and evaluation in a business context. Through hands-on learning experiences, students will gain an in-depth understanding of the popular tool of data analytics, enabling them to effectively analyse and interpret data and communicate insights clearly and effectively to inform decision-making.

Intended Learning Outcomes of Course

By the end of this course, students will be able to:

1. Evaluate the relevance of business intelligence concepts and data types in a business context.

2. Apply appropriate analytics methods to solve complex business problems.

3. Justify analytics method selection based on their impact on business outcomes.

4. Effectively process, summarise, and visualise complex business data using software to communicate insights and inform decision-making.

5. Design and implement an innovative business intelligence solution that integrates quantitative methods and machine learning techniques to address business challenges and opportunities.

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.