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BU593A: BIG DATA ANALYTICS, VISUALISATION AND BUSINESS APPLICATIONS (2021-2022)

Last modified: 31 May 2022 13:05


Course Overview

This module introduces students to big data, analytics and visualisation linked to business applications. The module also enables students to solve a variety of complex data-driven business problems using computer software tools, examples R and Gephi. The focus of the module thus is twofold: 1) building relative theoretical understandings, 2) and practice analytics for data-driven decision making for business operations and problems.

Course Details

Study Type Postgraduate Level 5
Session Third Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus Aberdeen Sustained Study No
Co-ordinators
  • Professor Pervaiz Akhtar

What courses & programmes must have been taken before this course?

  • Any Postgraduate Programme
  • Master Of Business Administration In Business Analytics

What other courses must be taken with this course?

None.

What courses cannot be taken with this course?

None.

Are there a limited number of places available?

No

Course Description

The module emphasises two broad theoretical and practical domains, which are specified as follows:

Theoretical understanding: This part provides the theoretical foundations of big data, analytics, network analysis and unstructured data. It further strengthens the effective use of data visualisation techniques, digitisation and their links with business applications. The theoretical foundations are further linked with a variety of business domains such as supply chains, network analytics and operations management.

Practical business applications: Students learn how to explore and solve business problems using R and Gephi software platforms. Students are involved through workshops and they actively solve variety of exercises that prepare them to be data-driven managers and executives capable of utilising data, analytics and digital networks for optimising their business performance.

Associated Costs

DescriptionValue
Guest speakers GBP 200.00

Details for second half-session courses, including assessments, may be subject to change until 23 December 2022.

Contact Teaching Time

Information on contact teaching time is available from the course guide.

Teaching Breakdown

More Information about Week Numbers


Details for second half-session courses, including assessments, may be subject to change until 23 December 2022.

Summative Assessments

Design Project: Individual

Assessment Type Summative Weighting 100
Assessment Weeks Feedback Weeks

Look up Week Numbers

Feedback

3000 words individual project. Feedback will be provided within 3 weeks of submission.

Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualRememberDemonstrate conceptual understanding of big data, analytics, digitisation and visualisation techniques.
FactualApplyLearn and apply software tools such as R and Gephi.
ProceduralAnalyseUtilise a variety of resources and techniques to systematically examine how managers and executives can utilise big data and analytics for business value creation interlinked with their performance.
ReflectionEvaluateCritically evaluate big data, analytics and visualisation aspects to explore and solve business problems.

Formative Assessment

There are no assessments for this course.

Resit Assessments

Design Project: Individual

Assessment Type Summative Weighting 100
Assessment Weeks Feedback Weeks

Look up Week Numbers

Feedback

3000 words individual project. Students will not be allowed to work on the same topic as they did for their first attempt.  Feedback will be given within 3 weeks of submission.

Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualRememberDemonstrate conceptual understanding of big data, analytics, digitisation and visualisation techniques.
FactualApplyLearn and apply software tools such as R and Gephi.
ProceduralAnalyseUtilise a variety of resources and techniques to systematically examine how managers and executives can utilise big data and analytics for business value creation interlinked with their performance.
ReflectionEvaluateCritically evaluate big data, analytics and visualisation aspects to explore and solve business problems.

Course Learning Outcomes

Knowledge LevelThinking SkillOutcome
ConceptualRememberDemonstrate conceptual understanding of big data, analytics, digitisation and visualisation techniques.
ReflectionEvaluateCritically evaluate big data, analytics and visualisation aspects to explore and solve business problems.
ProceduralAnalyseUtilise a variety of resources and techniques to systematically examine how managers and executives can utilise big data and analytics for business value creation interlinked with their performance.
FactualApplyLearn and apply software tools such as R and Gephi.

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