The Data in Business and Society module equips students with the skills and knowledge necessary to understand the role data, governance and ethics within the context of business and society. Students will learn to document and describe data architecture using appropriate data modelling tools and scope and deliver data analysis projects aligned with business priorities. Students will learn to report on data governance compliance and communicate data ethics decisions to diverse stakeholders, including senior clients and management. Upon completion of this module, students will possess the skills and knowledge to effectively analyse the information governance requirements, data protection standards, and data security regulations relevant to the UK.

Pre-requisite modules: None.

Co-requisite modules: None.

This module is a part of MSc Digital and Technology Solutions (Integrated Degree Apprenticeship) programme. It cannot be taken as an elective by students on other programmes.

The apprenticeship standard and other documentation relating to the Level 7 Digital and Technology Solutions (Data Analyst Specialist) Apprenticeship can be found here: https://www.instituteforapprenticeships.org/apprenticeship-standards/digital-and-technology-solutions-specialist-integrated-degree/

The module aims to provide you with the skills and knowledge to effectively analyse the information governance requirements, data protection standards, and data security regulations relevant to the UK.  You will learn to report on data governance compliance and communicate data ethics decisions to diverse stakeholders, including senior clients and management. The module will offer you an opportunity to acquire knowledge of data handling practices, documenting and describing data architecture using appropriate data modelling tools, and ethical and societal implications of data management strategies within business planning.

On successful completion of this module you should be able to:

Module Specific Skills and Knowledge

Discipline Specific Skills and Knowledge

Personal and Key Transferable / Employment Skills and Knowledge

Whilst the module’s precise content may vary from year to year, an example of an overall structure is as follow:

• How businesses use data to build, understand and report their strategic goals
• Applying current concepts in data and analytics to real examples
• Using ‘Design Thinking’ to create information management systems
• Understanding the legal, ethical and governance considerations around use and analysis of data in social and business contexts. Specific topics will include:
• Data projects. Using design thinking techniques to understand organisational problems in data management and scope solutions to these.
• Workshop on “what are data?”. Big data, small data and the challenge of capturing the long tail of research.
• Group discussions around research project topic.
• Workshop on data storage and archiving.
• Workshop on data dissemination, curation and Open Data, the limits of automation, and the challenges of making data accessible and re-usable.
• Presentations on research projects, group discussion of data challenges within different types of businesses with varying customer base.
• Data protection and legal frameworks for data collection, storage and analysis.

Basic reading:

• Schutt, R. and Neill, C. (2014) Doing Data Science: Straight Talk from the Frontline, O'Reilly
• Boyd, D. and Crawford, K. (2011) Six Provocations for Big Data. A Decade in Internet Time: Symposium on the Dynamics of the Internet and Society, Electronic Elsevier
• Kitchin, R. (2013) The Data Revolution, Sage.
• Fleming L.E., (2012) Big Data in Environment and Human Health: Challenges and Opportunities, Oxford University press.
• Borgman, C.L. (2015) Big Data, Little Data, No Data, MIT press.
• Provost, F. and Fawcett, T. (2013) Data Science for Business, O'Reilly.
• Mayer-Schonberger V. and Cukier K. (2013) Big data: a revolution that will transform how we live, work and think, Murray.
• Science International (2015). Big Data in an Open Data World.
• Hey et al. (2009) The Fourth Paradigm, Microsoft Publishing.
• Hine, C. (2006) ‘‘Databases as Scientific Instruments and Their Role in the Ordering of Scientific Work.’’ Social Studies of Science 36 (2): 269-98.
• Dove, E.S., et al. (2015) “Genomic Cloud Computing: Legal and Ethical Points
• Dove, E.S., et al. (2016) “Ethics Review for international Data-Intensive Research” Science 351 (6280): 1399–1400. doi:10.1126/science.aad5269.
• Burton, P.R., et al. (2015) “Data Safe Havens in Health Research and Healthcare” Bioinformatics 31 (20): 3241–48. doi:10.1093/bioinformatics/btv279.
• Boulton, G., et al. (2012) “Science as an Open Enterprise.” 02/12. London: The Royal Society Science Policy Centre.

Reading list for this module: