Business Analytics, MSc

University of Greenwich

This module will provide a foundation in business data analytics and visualisation based on data curation and statistical analysis. Further, the module will introduce students to the basic data analysis concepts and techniques that facilitate making decisions from rich data sets. Alongside the teaching of analytic tools and skills, students will be provided with an opportunity to discuss diverse issues around data analytics, such as information, communication and technologies (ICT), behaviours, organisations, policies, ethics and security, and how business analytics and visualisation can influence decision-making.

This module equips students with the statistical and econometrics knowledge. Equipping the students with econometrics skills will enhance the students’ understanding of managerial decisions and evaluate economic phenomena considering the theory and observations which are key skills needed in business analytics. Students will learn how to apply statistical techniques to the analysis of business data using statistical software, and develop the ability to recognise the most appropriate analytical approach for the analysis of real business problems.

This module will introduce students to the main data mining methods used in business analytics. With an emphasis on data mining with Python, students will focus on the analytical techniques that support the analysis of business and economic phenomena. Students will learn how to organize and analyse business and economic data available from different online sources.

1. Introduce students to the main tools and techniques that form part of the digital economy. 2. To explore the different types of blockchain technology and their applications in the digital economy. 3. To develop students' ability to evaluate and critically analyse the potential of blockchain technology for solving business problems and challenges.

The aims of the module are for students to 1. critically examine the legal and ethical implications of collecting big data and utilizing machine learning algorithms; 2. acquire comprehensive knowledge and understanding of the regulations and guidelines that govern data collection, as well as the ethical principles that should guide decision-making around the use of big data and machine learning; and 3. Enable students to act autonomously and critically on decisions regarding collecting big data and utilizing machine learning.

This module aims to provide learners with the essential academic and soft skills required to succeed in their studies and career.

In that context, the aims of this module are to - Introduce the fundamental business theories and concepts. - Appreciate and critically evaluate the complexities of doing business in a more digitalised world. - Develop the awareness and capability in data-driven decision making in business.

The aim of this module is to equip students with an understanding of the key factors that drive innovation, including the impact of digital technologies and big data methods. Students will learn how to assess digital technologies that influence innovation and understand the role of big data in the innovation process. They will also learn how to use data analytics methods and problem-framing techniques to ground innovative ideas in rigorous analysis and feasibility. By doing so, students will be able to make informed decisions about which ideas to pursue and how to prioritize resources for innovation efforts. Overall, this module will help students develop a structured and evidence-based approach to innovation, which will be useful for them in their future careers as well as for organizations looking to foster a culture of innovation.

The aim of this module is to provide students with a critical understanding of the concepts and techniques of Machine Learning, with a focus on models and algorithms for regression, classification, clustering, and probabilistic classification. By the end of the module, students will be able to implement and evaluate different Machine Learning models and apply these concepts and techniques to real-world problems. They will be able to identify the appropriate model for a given problem based on the type of data and the desired outcome, as well as to evaluate the performance of different models based on various performance metrics.

This module aims to equip students with a collection of standard data processing methods to flexibly explore, examine, and transform raw and unstructured datasets into meaningful ones that can inform business decision-making. Students will develop their hands-on experience on specific daily tasks of a business analyst and build up potentially reproducible approaches when confronting real-world business problems. This module also provides programming tools to support the analysis of big data. In that respect, this module sits alongside and complements two other modules, Big Data Analytics and Visualisation and Machine Learning.

Social media are powerful communication tools, but they are also increasingly used for understanding the behaviour of their customers. This module helps students to explore and collect data from multiple social media platforms and apply analytical methods to gain novel insights from social media data to support business objectives.