Masters in Information Management & Digital Business – Digital Innovation

Aims:

This module introduces key concepts, techniques, and tools for business data analytics. Data analytics is a fundamental tool for any organisations to make strategic use of their data assets and enable data-driven decision making. The module will cover concepts in data management, basic statistics and analytics, as well as tools used in business data analytics.

Outline Content:

• Data analytics and data-driven decision making
• Descriptive analytics
• Data visualisation principles
• Tools for data visualisation
• Predictive analytics
• Advanced tools for data analytics
• Principles of databases
• Data management
• Programming for data analytics
• Data analytics solutions development

Academic authors

Dr Markos Kyritsis

Outline content:

• • Understand the signs and types of signs (indices, icons and symbols) used in human communication and computer information systems, from semiotic and other relevant perspectives
  • Investigate the characteristics of organisational needs in the era of e-enterprise and the potential IT capabilities required to support business objectives and functions
  • Study the methods and techniques for aligning business and IT strategies, business and IT planning, requirements analysis and determination
  • Select appropriate theories, methods and techniques for application in the design and development of IT solutions

This module develops critical digital knowledge and skills in digital concepts, leadership, teambuilding, capability and change planning and control to support the development of a digital technology solutions in businesses. It integrates leadership and e-leadership principles with a knowledge of digital technology and the practice of leading digital solution approaches and teams in a variety of leadership types at strategic level required by a business or consulting client. It provides appropriate capability and analysis tools and techniques to enable students to identify, manage and resolve digital leadership and supporting digital technology issues and enables the development of appropriate digital leadership approaches necessary to support digital business technology and related consulting situations.

This module is concerned with the use of existing and cutting-edge technologies and innovations to provide digital business solutions for businesses. It focuses on values-based innovation, digital business ecosystems and platform ecosystems, and employs the emerging service science and service logic/thinking approaches to the development of the digital business solutions. It covers innovations in processes, products, technology, services, and business models, as well as methods and models to create new business value in highly competitive and technology-rich environments.

Aims:
This module aims to provide students with the opportunity to undertake a substantial research project, drawing on the knowledge and skills acquired from past experience and from the taught part of the MSc programme. It enables students to learn how to conduct a research project, develop problem-solving and critical-analytical skills, and manage research activities. There are opportunities to carry out the project with external organisations.

Outline content:

• Progression from the Research Methods module (research proposal, literature review, and project planning)
• Regular meetings with supervisors
• Interim report
• Dissertation report
• Oral presentation

Aims:

Given the availability of large amount of both structured and unstructured data in business, there is a need for organisations to assess how effectively Big Data can be utilised for business. The aim of this module is to evaluate the business value in utilising Big Data and develop information management solutions with an appreciation of business analytics methods and technologies.

Outline content:

• Business opportunity in the era of Big Data – case studies
• Business analysis for big data and business intelligence
• Methods, techniques and tools for Big Data
• Data and information management for Big Data
• Big Data visualisation
• Developing a Big Data strategy
• Professional, leadership and ethical issues in Big Data solutions

Aims:
This module is concerned with how business intelligence and data mining techniques can be used for managerial decision-making. It aims to provide students with the essential data mining and knowledge representation techniques used to transform data into business intelligence. Application areas covered in this module include marketing, customer relationship management, risk management, personalisation, etc.

Outline content:

• Concepts of business intelligence and data mining
• Overview of various data mining techniques
• Types of data, data cleaning, data integration and transformation, data reduction
• Classification and predictive modelling
• Cluster analysis for generating patterns of data and structuring business intelligence
• Association rule mining and market-basket analysis
• Business intelligence implementation, integration and emerging trends

Aims:
This module aims at developing the understanding of business service design regarding service thinking concept and business performance management in the digital economy. This module will equip the student with the knowledge of business service innovation with a focus of organisational, business architecture and service system design and performance management in the new service context.

Outline content:

• Service and service innovation concept, framework and approaches for business service deign
• Organisational design and business model generation in the service context
• Performance management for maintaining an organisation’s quality, e.g. concepts of performance metrics, and their alignment with corporate strategy, critical success factors, key performance indicators (KPIs)
• Performance assessment methods and techniques, e.g. benchmarking, balanced score card, total quality management
• Multi-sided metrics to assess business service performance

Aims:
This module develops knowledge and skills in the use of consulting tools for enterprise modelling and analysis. It is taught in three key parts, which include frequent tutorials, examples and a case study developed in conjunction with Capgemini consultants. This three-part approach welds business and technology techniques with consulting methods to enable students to both identify and resolve current and future issues affecting organisations.

Outline content:

• Part 1 addresses the theory of consulting, consulting structure, generic consulting methods and tools
• Part 2 focuses on understanding and applying examples of specific framework tools and techniques, building on IRC and Capgemini developed methods
• Part 3 ‘consulting in practice’ involves case analysis and presentations by students to practicing consultants, applying relevant techniques to practical business-technology problems
• Students undertake a team-based case study relating to actual consulting practice, led by practising consultants

This module focuses on knowledge and hands on skills to leverage information technology, data analytics and machine learning skills in healthcare service delivery, clinical research, hospital operational management and public health. The students will have blended learning experience including in-class lectures, machine learning and data analytics exercise as well as case studies from NHS hospitals, community and social care organisations, local authority and companies who provide digital health and data analytics solutions, in UK and internationally.

Aims:
This module aims to enable students to understand management theories and project management practices such as Agile and PRINCE2. Students will be able to carry out project planning with different methods, and incorporate risk management and quality control techniques. Students will also be able to understand the characteristics of IT projects and improve the success rate of project management.

Outline content:

• • Theories and principles of project management
  • Project management in organisations
  • Methodologies (e.g. Agile and PRINCE2) for project management
  • Project planning and delivery (e.g., estimating, scheduling, resourcing, and monitoring)
  • Risk management
  • Quality control mechanisms