COMP60711 Data Engineering syllabus 2017-2018
All application areas are witnessing the "data deluge", i.e. the ever growing amount of digital data available as part of day-to-day activities in business, science, education, entertainment, etc. Indeed "Big data" has become part of modern vernacular. Engineering, managing and analysing such data is a key for success of all organisations. In addition to the need to work with huge volumes of data, current applications are also challenged with multi-modal data, including un- and semi-structured data, image and video data, spatial and temporal data, etc.
This module will examine the entire data life cycle, including data creation, modelling, acquisition, representation, use, maintenance, preservation and disposal. As the majority of data is stored in databases, the module will examine various database engineering approaches to support data management, including database design, data warehousing, maintenance and analytics. Data standards and data quality will be examined and the challenge of "big datasets" will be considered.
- An overview of the data life cycle
- Data engineering, modelling and design techniques
- Data storage and warehousing
- Data access and maintenance
- Big Data, Map-Reduce, Hadoop
- Data analytics and visualisation
- Engineering non-traditional data types
- Data standards and data quality
Feedback methodsRegular coursework, returned marked with feedback
- Analytical skills
- Problem solving
- Written communication
|Programme outcome||Unit learning outcomes||Assessment|
|A1||Have an understanding of the data life cycle.|
|A2 C4 D4||Have an understanding of data engineering techniques, and be able to perform and document large-scale data engineering for a given task, comprising various multimodal data types.|
|A2||Have an understanding of technical, ethical and societal issues related to data engineering, storage, access and maintenance.|
|A2 B1 B3 C4||Understand the main principles of data analytics and explain how it can be used in various application areas.|
|A2 B1 D3 D4||Demonstrate an understanding of relevant standards and best practice in data engineering and be able to identify, understand and articulate the shortcomings of existing data engineering practices and to suggest, in broad terms, possible strategies and approaches that might be used to overcome them.|
COMP60711 does not have a specified reading list.
Course unit materials
Links to course unit teaching materials can be found on the School of Computer Science website for current students.