Nursing in Leadership and Quality Healthcare – MSc/Postgrad Diploma

Data analytics is an area of increasing importance and interest to organisations. Data analytics techniques offer huge potential in the creation of new knowledge products and services in addition to the enhancement of existing products and services. This module addresses the application of data analytics techniques to real-world business problems and the preparation of data for such scenarios.

This module will teach students the importance of data pre-processing and data exploration. Students will prepare data for analysis using a range of advanced data processing techniques and software tools.

Students taking this module will acquire the computer programming skills necessary to analyse and manipulate data sets. This module will introduce key programming concepts using programming languages designed specifically for data analytics.

This module provides the student with the skills in areas such as entity modelling, normalisation and database design. In addition, significant time will be devoted to utilising the SQL language to operationalise the output of the design process, manage data and manage security in a modern relational database management system.

This module will introduce students to the use and role of probability models and statistical inference in data analytics. Laboratory work will give the student experience in applying probability and statistical models to real-world data.

Advanced Databases will build on the Relational Databases module from Semester 1 and give students the opportunity to acquire a thorough understanding of stored procedures in the context of an enterprise database environment. A database programming language will be taught and students will study the key language constructs such as variables, conditional structures, loops, in addition to other more advanced topics such as cursors, functions, and packages. Another key strand in this module is growing importance of NoSQL and other emerging database technologies, students will get an in depth appreciation of those technologies, and their role in an era of massive data storage and processing challenges. In particular, the challenges around distributed databases, transaction processing and data consistency will contrast strongly with some of the topics covered in Semester 1. Finally, the legal, social, and ethical issues and responsibilities for managers and users of databases will be a key backdrop for data analytics students and complement what they are studying in several other modules on the programme.

This module develops student skills in data visualisation by introducing various data visualisation techniques. Students will learn how to explain the insights obtained from large data sets using data visualization techniques. One of the essential skills in data analytics is the ability to tell a story, visualizing data and findings. Students will learn how to use various techniques to present data visually, obtain a better understanding of the data, and make more effective decisions.

This module aims to introduce students to the key concepts involved in research and to develop their understanding of the uses and relevance of the major methodologies employed. The material covered in this module will form the basis for the research dissertation element of the MSc in Data Analytics programme, with one of the key outcomes of this module being a valid and robust research proposal for research in the area of Data Analytics.

The project builds on the Research Methods module, where the research proposal will have been developed and submitted. The dissertation will consist of 20,000 words, excluding appendices. As the capstone component of the programme, this element will help integrate the curriculum content, and working in conjunction with an approved industry partner, deliver a significant body of work that will contribute to the body of knowledge in the field of data analytics. The dissertation will draw on analytical and evaluative competences based upon knowledge and skills developed during the programme. The exercise also provides an opportunity for students to develop their interests in a particular area of Data Analytics, while working with the industry partner and to demonstrate an ability to undertake individual research in an ethical and methodologically sound manner.