Module Code: H8DG
Long Title Data Governance
Title Data Governance
Module Level: LEVEL 8
EQF Level: 6
EHEA Level: First Cycle
Credits: 5
Module Coordinator: Sophie Flanagan
Module Author: ORLA LAHART
Departments: School of Computing
Specifications of the qualifications and experience required of staff

Master’s and/or PhD degree in computing or cognate discipline. May have industry experience also.

Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Analyse the concepts of data governance, data management and data strategies and critically evaluate them in the context of organizational data policies, processes and procedures.
LO2 Comprehend the regulatory and legislative requirements around data management and stewardship, synthesize their implications for organisational data management, processes and procedures, and apply their implications for the collection, storage, use and dissemination of organizational data resources.
LO3 Comprehend the ethical underpinnings of good data governance, in the context of an overall framework for data management and apply the resultant framework to emerging areas of technological development
LO4 Analyse the range of internal and external stakeholders concerned with the design and implementation of an effective data governance strategy. Comprehend and evaluate the role and responsibilities across different organizational levels and functional areas related to the data management and governance functions such as Chief Data Officer.
LO5 Apply a range of tools and techniques for the effective governance, management integrity and security of data resources in an organizational context and evaluate their application in the context of specific case studies and scenarios.
Module Recommendations

This is prior learning (or a practical skill) that is required before enrolment on this module. While the prior learning is expressed as named NCI module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).

No recommendations listed
Co-requisite Modules
No Co-requisite modules listed
Entry requirements

Use programme level text


Module Content & Assessment

Indicative Content
Introduction to Data Governance
Course overview; Purpose of Data Governance; Evolving role of data in a modern organisation; Data risks; Costs, Benefits and ROI from data holdings; Relationship to other course modules.
Concepts and Definitions
To cover the scope of Data Governance along with an explanation of other related concepts such as Data Strategies, Principles and Frameworks. Will consider Data Governance from Strategic, Functional and Operational/Technical levels within an organisation.
Stakeholders, Roles and Responsibilities
To include information on the range of stakeholders (internal, external) that an organisation should be aware of as well as a more detailed exposition of the roles and responsibility of a range of data professional roles within an organisation.
Data Protection Legislation and Regulatory environment
An outline of the key legislative and regulatory measures across a range of jurisdictions and the role of data protection authorities. Evaluate the implications of legislation for data professionals as well as illustrative Case Studies.
Ethical considerations for data analytics
Rationale for studying ethical considerations in Data Governance together with exposition of ethical dilemmas, frameworks and case studies for addressing them.
Data Governance – contemporary case studies
A range of contemporary data governance issues covering data protection, usage of social media data and technical area. A guest speaker with expertise in the area will make a keynote presentation (subject to availability).
Assessment Breakdown%


Full Time

Assessment Type: CA 1 % of total: 30
Assessment Date: n/a Outcome addressed: 1,2
Non-Marked: No
Assessment Description:
Group assignment where each team has to argue a proposition related to the items covered in the first part of the course in a debate style format.
Assessment Type: CA 2 % of total: 70
Assessment Date: n/a Outcome addressed: 1,2,3,4,5
Non-Marked: No
Assessment Description:
Application of learning from course to analyse a case study organisation and design a data governance framework and strategy through the preparation of a report and infographic.
No End of Module Assessment
No Workplace Assessment
Reassessment Requirement
Coursework Only
This module is reassessed solely on the basis of re-submitted coursework. There is no repeat written examination.
Reassessment Description
This module is reassessed solely on the basis of re-submitted coursework. There is no repeat written examination.

NCIRL reserves the right to alter the nature and timings of assessment


Module Workload

Module Target Workload Hours 0 Hours
Workload: Full Time
Workload Type Workload Description Hours Frequency Average Weekly Learner Workload
Lecture Weekly Lecture 24 Every Week 24.00
Tutorial Weekly Lab 12 Every Week 12.00
Independent Learning Research 89 Every Week 89.00
Total Weekly Contact Hours 36.00

Module Resources

Recommended Book Resources
  • Harkish Sen. (2019), Data Governance, 1. 6, Technics Publications, p.208, [ISBN: 1634624785].
  • Mike Loukides,Hilary Mason,Dj Patil. (2018), Ethics and Data Science, 5, [ISBN: 9781492078227].
  • Dama International. DAMA-Data Management Body of Knowledge, 2nd. 17, p.628, [ISBN: 9781634622349].
Supplementary Book Resources
  • Katherine O'Keefe,Daragh O Brien. (2018), Ethical Data and Information Management, Kogan Page, p.344, [ISBN: 0749482044].
  • Rupa Mahanti. (2019), Data Quality: Dimensions, Measurement, Strategy, Management and Governance, Quality Press, p.526, [ISBN: 9780873899772].
Supplementary Article/Paper Resources
  • Fiesler, Casey; Proferes, Nicholas. (2018), “Participant” Perceptions of Twitter Research Ethics, Social Media + Society, Vol. 1, Issue 4, p.14, [ISSN: 2056-3051],
  • Samuel, Gabrielle Derrick, Gemma E. van Leeuwen, Thed. (2019), The Ethics Ecosystem: Personal Ethics, Network Governance and Regulating Actors Governing the Use of Social Media Research Data, Minerva, 57, [ISSN: 15731871],
  • Siau, Keng Wang, Weiyu. (2020), Artificial Intelligence (AI) Ethics, Journal of Database Management, 31, [ISSN: 1063-8016].
  • Kemper, Jakko Kolkman, Daan. (2019), Transparent to whom? No algorithmic accountability without a critical audience, 22.
  • Hand, David J.. (2018), Statistical challenges of administrative and transaction data, Journal of the Royal Statistical Society. Series A: Statistics in Society, 121, [ISSN: 1467985X].
Other Resources
Discussion Note: