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Academic Handbook MSc Artificial Intelligence and Technology Leadership

Data-Driven Transformation Course Descriptor

Course code LCSCI7231 Discipline Computer Science
UK Credit 15 US Credit NA
FHEQ level 7 Date approved June 2023
Core attributes N/A
Pre-requisites None
Co-requisites None

Course Overview

This course will provide a broad and in-depth understanding of modern data-driven business processes, digital transformations and strategy. It introduces students to business concepts, terminology and strategic frameworks for analysing the external and internal business environments and developing digital transformation strategies in the highly competitive data-driven economy. Through case studies and readings learners will use originality in solving problems and will develop the skills necessary to act autonomously in planning and implementing digital and technology strategies and transformations, including effective data visualisation. The course will examine how to monitor technology-related market trends and research and collect competitive intelligence. There is a particular focus on sustainability in terms of societal and environmental impact. Students will be able to present strategic arguments in a structured manner and apply this to the delivery of a compelling digital transformation strategy.

Course Aims

The aims of the course are to: 

  • To understand strategic digital transformation principles and concepts
  • To develop a critical understanding of business requirements and data requirements.
  • To develop the skills to identify, plan and deliver digital transformation.
  • To critically evaluate and analyse evidence-based business intelligence.
  • To apply design principles and theories to develop effective data visualisation.
  • To develop the knowledge and skills to create effective data-driven communication strategies and technology roadmaps to both technical and non-technical audiences.

Learning Outcomes

On successful completion of the course, students will be able to:

Knowledge and Understanding

K2d(i) Comprehensively understand the underpinning principles of data-driven transformation.
K2d(ii) Systematically understand how to monitor market trends and collect competitive intelligence.
K4d Comprehensively understand the strategic importance of data-driven business strategy and technology roadmap.

Subject Specific Skills

S1d Use theory, tools and frameworks to critically evaluate the business intelligence and develop transformation strategies to improve business performance.
S2d Critically evaluate business literature to compare and critique different approaches to data-driven business strategy
S3d Critically evaluate and create effective communication plans based on rigorous data analysis.

Transferable and Professional Skills

T1d Evaluate and develop effective data-driven communication strategies.
T2d Consistently display an excellent level of technical proficiency in written English and command of scholarly terminology, so as to be able to deal with complex issues in a sophisticated and systematic way.
T3d(i) Use self-direction and originality in problem solving
T3d(ii) Identify, critique and synthesise complex information from a range of sources.

Teaching and Learning

This course has a dedicated Virtual Learning Environment (VLE) page with a syllabus and range of additional resources (e.g. readings, question prompts, tasks, assignment briefs, discussion boards) to orientate and engage you in your studies.

The scheduled teaching and learning activities for this course are:

Lectures/Labs. Contact hours are typically a mix of weekly lectures and lab sessions, totalling up to 50 scheduled hours:

  • Version 1: All sessions in the same sized group, or
  • Version 2: most of the sessions in larger groups; some of the sessions in smaller groups

Faculty hold regular ‘office hours’, which are opportunities for students to drop in or sign up to explore ideas, raise questions, or seek targeted guidance or feedback, individually or in small groups.

Students are to attend and participate in all the scheduled teaching and learning activities for this course and to manage their directed learning and independent study.

Indicative total learning hours for this course: 150

Assessment

Both formative and summative assessment are used as part of this course, with formative opportunities typically embedded within interactive teaching activities delivered via the VLE.

Summative

AE: Assessment Activity Weighting (%) Duration Length
1 Practical Tasks 50% N/A  
2 Written Assignment 50% N/A 2,000 words +/- 10% excluding data tables

Further information about the assessments can be found in the Course Syllabus.

Feedback

Students will receive formative and summative feedback in a variety of ways, written (e.g. marked up on assignments or via the VLE) or oral (e.g. as part of interactive teaching sessions or in office hours).

Indicative Reading

Note: Comprehensive and current reading lists for courses are produced annually in the Course Syllabus or other documentation provided to students; the indicative reading list provided below is used as part of the approval/modification process only.

Books

  • Saloner, G. Shepard, A. and Podolny, J.M. (2001). Strategic Management. New York : Wiley
  • Neugebauer, R. (2019). Digital Transformation. Berlin, Heidelberg : Springer
  • Hedin, H., Hirvensalo, I. and Vaarnas, M. (2011). The Handbook of Market Intelligence : Understand, Compete and Grow in Global Markets. West Sussex, England : Wiley
  • Knaflic, C.N., (2015). Storytelling with data: A data visualization guide for business professionals. John Wiley & Sons.
  • Pham, Pham, D. K., & Pham, A. (2018). From Business Strategy to Information Technology Roadmap : A Practical Guide for Executives and Board Members (1st edition). Productivity Press.

Indicative Topics

Note: Comprehensive and current topics for courses are produced annually in the Course Syllabus or other documentation provided to students. The indicative topics provided below are used as a general guide and part of the approval/modification process only.

  • Digital Transformation
  • Data Lifecycle and Business Requirements
  • Business Process Analysis and Reengineering
  • IT Strategy
  • Technology Roadmaps
  • Design Principles and Theories
  • Data Visualisation
  • Persuasive Communication with Data

Version History

Title: LCSCI7231 Data-Driven Transformation

Approved by: Academic Board

Location: Academic Handbook/Programme specifications and Handbooks/ Postgraduate Programme Specifications/

Version number Date approved Date published Owner Proposed next review date Modification (As per AQF4) & category number
1.0 June 2023 June 2023 Dr Alexandros Koliousis April 2028  
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