MQM2DAS-Data Analytics Strategy in Business

Module Provider: Business Informatics, Systems and Accounting
Number of credits: 20 [10 ECTS credits]
Terms in which taught: Spring term module
Non-modular pre-requisites:
Modules excluded:
Current from: 2020/1

Module Convenor: Prof Keiichi Nakata


Type of module:

Summary module description:

This module focusses on the strategic use of data analytics in business in the era of Big Data. Given the availability of large amounts of data in business and organisation, there is an increasing need for organisations to assess how effectively data analytics and relevant emerging technologies can be utilised for business. In this module, students consider how organisations can benefit from Big Data and analytics, and analyse business and technological requirements to create value though these technologies. Students will also explore recent developments in technologies surrounding Big Data and data analytics such as text analytics, visual analytics and artificial intelligence, and assess types of tools that can be utilised, including the evaluation and use of state-of-the-art tools. Students will also assess the legal and ethical implications of data analytics in business.


The aim of this module is to evaluate the business value in utilising data analytics and develop information and data management solutions with an appreciation of data analytics methods and technologies. It also develop understanding of the legal, social and ethical concerns involved in data management and analysis.

Assessable learning outcomes:

Assessable learning outcomes:


Upon successful completion of this module, students should be able to:


  • Assess the business opportunity and value creation through the utilisation of business data analytics by analysing the business environment and requirements;

  • Critically assess suitable data analytics technologies and business analytics approaches;

  • Formulate a solution for achieving value through data analytics;

  • Scope and deliver data analysis projects, in response to business priorities, create compelling business opportunities reports on outcomes suitable for a variety of stakeholders including senior clients and management;

  • Demonstrate the awareness and understanding of the information governance requirements that exist in the UK, and the relevant organisational and legislative data prote ction and data security standards that exist.

  • Assess and address the organisational and technical impact of implementing the solution, including the legal, social and ethical concerns involved in data management and analysis;

Additional outcomes:

Upon successful completion of this module, students should be able to:

  • Critically assess the suitability of a range of business analytics tools against a set of requirements;

  • Become familiar with state-of-the-art developments and data analytics tools

Outline content:

  • Introduction; Business opportunity of data analytics in the era of big data

  • Big data and data analytics strategy

  • Business analysis for data analytics and business intelligence

  • Methods, techniques and tools for big data and analytics

  • Developing a data analytics strategy

  • Big Data visualisation

  • Strategic use of artificial intelligence and machine learning technologies

  • Prof essional, leadership, social, legal and ethical issues in implementing data analytics solutions

  • Emerging issues and impacts of big data analytics

Brief description of teaching and learning methods:

This module combines lecture, seminars and practical workshops to develop Big Data strategies. It also uses state-of-the-art analytics tools as part of developing a Big Data solution in business as a team project.

Contact hours:
  Autumn Spring Summer
Lectures 14
Work-based learning 24
Guided independent study:      
    Wider reading (independent) 30
    Wider reading (directed) 30
    Advance preparation for classes 8
    Other 30
    Preparation of practical report 40
    Group study tasks 24
Total hours by term 0 200 0
Total hours for module 200

Summative Assessment Methods:
Method Percentage
Written assignment including essay 100

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:

Assessment will consist of a written coursework assignment (up to 20 pages of A4) (100%) due three weeks after the completion of the learning content. In completing the coursework assignment, students will be expected to produce a data analytics strategy for a particular business context, based on which an individual report is produced. The assignment will provide students an opportunity to communicate critically and concisely their findings which demonstrate their extended understanding of the subject.

Formative assessment methods:

Penalties for late submission:
Penalties for late submission on this module are in accordance with the University policy. Please refer to page 5 of the Postgraduate Guide to Assessment for further information:

Assessment requirements for a pass:

Students will be required to obtain a mark of 50% or above.

Reassessment arrangements:

Additional Costs (specified where applicable):

Last updated: 27 August 2020


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