MSc Data Engineering

This module is NOT available unless you have successfully completed 120 Credits.
MSc Dissertation

This module is only available for students enrolled on to MSc Data Science or MSc Data Engineering.

The module presents a balanced approach to the subject area by addressing both the theory and practice of Business Intelligence and reporting in enterprise systems. The aim of this module is to develop a deep understanding of enterprise information systems and their role in business processes alongside practical skills in business intelligence reporting and dashboard design.
It includes: Evaluation of the impact that Enterprise Information Systems can have within organisation business processes; An assessment of the impact that they have on the efficiency and effectiveness of organisations and supply chains; Fundamentals of business intelligence, such as data warehousing and data mining; The role of performance dashboards in performance management and measurement in organisations; The sourcing and extraction of data and the analysis and development of intelligence.

This module is only available for students enrolled on to MSc Data Engineering.

The challenges of contemporary data acquisition and analysis have been characterised as “the four V’s of Big Data” (volume, variety, velocity and validity). These require the use of specialised data storage, aggregation and processing techniques. This module introduces a range of tools and techniques necessary for working with data in a variety of formats with a view to developing data driven applications. The module focuses primarily on developing applications using the Python scripting language and associated libraries and will also introduce a range of associated data storage and processing technologies and techniques.

The module covers the following topics:

• Data types and formats: numerical and time series, graph, textual, unstructured,
• Data sources and interfaces: open data, APIs, social media, web-based
• NoSQL databases such as document (MongoDB), graph and key value pair
• Techniques for dealing with large data sets, including Map Reduce
• Developing Data Driven Applications in Python