Skip to main content
 

COMP41915: Data Analytics in Action

It is possible that changes to modules or programmes might need to be made during the academic year, in response to the impact of Covid-19 and/or any further changes in public health advice.

Type Tied
Level 4
Credits 15
Availability Available in 2023/24
Module Cap None.
Location Durham
Department Computer Science

Prerequisites

  • None

Corequisites

  • None

Excluded Combinations of Modules

  • None

Aims

  • To provide an appreciation of descriptive and prescriptive business-analytics techniques.
  • To provide knowledge of, and ability to apply, a range of descriptive and predictive business-analytics techniques.
  • To implement descriptive and predictive business-analytics models using appropriate software.
  • To provide knowledge of, and ability to apply, data visualisation using appropriate software.

Content

  • Descriptive techniques such as data visualisation, data analysis, and descriptive statistics.
  • Predictive techniques such as clustering and classification.

Learning Outcomes

Subject-specific Knowledge:

  • By the end of the module students should:
  • Have in-depth knowledge of a range of descriptive and predictive business-analytics techniques and be able to apply them critically to management problems.
  • Have an understanding of the applicability and limitations of descriptive and predictive business-analytics techniques;

Subject-specific Skills:

  • By the end of the module students should be able to:
  • Implement descriptive and predictive business-analytics models using appropriate software packages;
  • Interpret the results of descriptive and predictive business analytics models and their relevance for companies.

Key Skills:

  • Effective written communication
  • Planning, organising and time-management
  • Problem solving and analysis
  • Interpreting and using data
  • Making effective use of communication and information technology
  • Data visualisation

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • Learning outcomes are met through classroom-based workshops, supported by online resources. The workshops consist of a combination of taught input, computer practical sessions, group work, case studies and discussion. Online resources provide preparatory material for the workshops typically consisting of directed reading and video content.
  • The formative assessment consists of classroom-based exercises involving individual and group analyses and presentations on specific business situations/problems relevant to the learning outcomes of the module.
  • The summative assessment is an individual business analytics project, which is designed to test the ability to formulate a problem, apply appropriate business-analytics techniques to analyse it, and critically interpret the results obtained.

Teaching Methods and Learning Hours

ActivityNumberFrequencyDurationTotalMonitored
Lectures101 a week2 hours20Yes
Computer workshops (max 25 students)41 every 2 weeks1 hour4Yes
Preparation and reading126 
Total150 

Summative Assessment

Component: CourseworkComponent Weighting: 100%
ElementLength / DurationElement WeightingResit Opportunity
Statistical modelling with Excel50 
Data handling and visualisation50 

Formative Assessment

The formative assessment consists of classroom-based exercises involving individual and group analyses and presentations on specific business situations/problems relevant to the learning outcomes of the module. Oral and written feedback will be given on a group and/or individual basis as appropriate.

More information

If you have a question about Durham's modular degree programmes, please visit our Help page. If you have a question about modular programmes that is not covered by the Help page, or a query about the on-line Postgraduate Module Handbook, please contact us.

Prospective Students: If you have a query about a specific module or degree programme, please Ask Us.

Current Students: Please contact your department.