Information Systems and Data Management for Business MSc

This module gives students knowledge and understanding of the concepts and theories of managing large data (i.e. Data warehouse, Data mining). Students will also explore technologies and algorithms for handling a large amount of data, i.e., data modelling, data projection and data transformation to discover knowledge from large data sets. The module is designed to apply the theories of decision-making and data analytics using some of the most widely used contemporary methods enabling modern business intelligence systems.  In particular, the module applies theories and practices of enterprise decision making, for example, statistical modelling, forecasting and trend analysis to tackle the challenges of uncertainty. 

This module will enable students to bridge the gap between advanced technology and practical business application. It focuses on demystifying AI and machine learning concepts, providing students with a clear understanding of how these tools can drive business innovation and efficiency. Through hands-on exercises and case studies, students will explore AI's role in predictive analytics, process automation, and customer insights. The module emphasises decision-making with AI, teaching participants to evaluate models, assess risks, and interpret outcomes effectively. Learners gain the skills to lead AI-driven projects and communicate technical ideas to diverse teams. This module empowers professionals to navigate the evolving landscape of technology and positions them as valuable contributors in AI-enabled workplaces. 

This module focuses on legal and ethical issues/challenges related to the use/deployment of emerging technologies in business. Emerging technologies include intelligent technologies (e.g., artificial intelligence, machine learning, internet of things), decentralised technologies (e.g., ledger technology, smart contracts and digital currencies) and immersive technologies (e.g., virtual reality and augmented reality). Students will gain knowledge and understanding of relevant key challenges/concerns associated with emerging technologies and the relevant legal and ethical frameworks impacting on the use/deployment of these technologies. They will also gain skills necessary to provide guidance and implement effective organisational policies/procedures to ensure responsible use/deployment of emerging technologies. 

This module will equip students with knowledge and understanding of Strategic Information System (SIS) and their development and implementation in response to corporate business initiatives. Emphasis will be on their integral role in an organisation’s strategic planning and competitiveness. Students will explore how competitive advantage can be gained by effectively aggregating, processing, and managing data to inform decision-making. Special focus will be given to new technologies and strategies used in new business models, with a particular emphasis on Business Intelligence (BI) and Analytics Systems. The strategic use of Social Media at the organizational level will also be stressed. In addition, students will acquire knowledge of Project Management highlighting the processes, tools and technologies used in the practice of managing successful projects, with particular focus on PRINCE2®. 

Information systems and data management facilitate digital business which leverages digital technologies and data as strategic assets to develop new competencies (e.g. innovative products, new business models, social media marketing etc) and maintain a competitive business advantage. The conduct of digital business and processing of data in that context, however, are subject to mandatory compliance with various regulatory frameworks, which is also an essential aspect of management. This module enables students to gain a critical understanding of relevant regulatory frameworks impacting on digital business and data use in the context of online business activities. These frameworks include compliance requirements for network security and information systems, digital platforms, data processing, internet intermediaries, online advertising and marketing, and related digital business activities. Students will also develop relevant competencies and skills to implement policies and practices to ensure effective regulatory compliance within a business context.

This module aims to equip students with the tools and techniques necessary to design and implement effective and efficient experiments in the context of computer science projects. It will also provide students with the skills required for statistical analysis, hypothesis testing, and presenting results within the scope of computational research and data-driven studies.

The primary aim of this module is to develop student’s employability skills and support their search for a placement. The module will include communication, team working, negotiation and problem-solving skills development as well as practical workshops on selection methods, CV's, cover letters, interview preparation and techniques. The module will also introduce students to other methods that will include aptitude test and assessment centres.

The objective of this module is to offer students a three-month (12-week) work placement that is directly applicable to their studies, encouraging them to engage in critical reflection on their learning through hands-on experience. Additionally, it seeks to develop students' intellectual and interpersonal abilities, thereby deepening their critical comprehension of real-world applications.

The objective of this module is to offer students an extended (minimum 36 weeks) work placement that is directly applicable to their studies, encouraging them to engage in critical reflection on their learning through hands-on experience. Additionally, it seeks to develop students' intellectual and interpersonal abilities, thereby deepening their critical comprehension of real-world applications.

Whether you are studying full or part-time – your course timetable will balance your study commitments on campus with time for work, life commitments and independent study.

We aim to make timetables available to students at least 2 weeks before the start of term. Some weeks are different due to how we schedule classes and arrange on campus sessions.

Typical weekly breakdown

Each of the four taught modules is allocated 3 hours of teaching per week and 9.5 hours for independent study.

Teaching vs independent study

In a typical year, you’ll spend about 1200 hours on your course.

Outside of teaching hours, you’ll learn independently through reading articles and books, working on projects, undertaking research, and preparing for assessments including coursework and presentations.

Learning terms

On-campus: This includes tutor-led sessions such as seminars, lab sessions and demonstrations as well as student-led sessions for work in small groups.

Independent study: This is the work you do in your own time including reading and research.

Part-time study

You can also study this course part-time over two years. You will complete two taught modules per academic year.

You will be based at our north London campus.

Your knowledge, understanding and skills is assessed via a range of assessment methods, such as: presentations, practical assessments, and coursework.

You'll evaluate your work, skills and knowledge and identify areas for improvement. Sometimes you'll work in groups and assess each other's progress. Each term, you'll get regular feedback on your learning.