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COMP60711 Data Engineering syllabus 2018-2019

COMP60711 Data Engineering

Level 6
Credits: 15
Enrolled students: 79

Course leader: John Keane

Additional staff: view all staff

Assessment methods

  • 60% Written exam
  • 40% Coursework
Sem 1 P1 Lecture 2.19 Tue 09:00 - 12:00 -
Sem 1 P1 Lab 2.25 (A+B) Tue 13:00 - 17:00 -
Themes to which this unit belongs
  • Data Engineering and Systems Governance


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
  • Data analytics application and algorithms
  • Engineering non-traditional data types
  • Data standards and data quality

Feedback methods

Regular coursework, returned marked with feedback

Study hours

Employability skills

  • Analytical skills
  • Problem solving
  • Research
  • Written communication

Learning outcomes

Programme outcomeUnit learning outcomesAssessment
A1Explain and apply the constituent steps of the data life cycle
  • Examination
A2 C4 D4Describe data engineering techniques; be able to apply and document large-scale data engineering for a given task, comprising various multimodal data types.
  • Examination
  • Lab assessment
A2Describe and apply technical, ethical and societal issues related to data engineering, storage, access and maintenance.
  • Examination
A2 B1 B3 C4Explain and apply the main principles of data analytics/ algorithms, and explain their application to various domains.
  • Examination
A2 B1 D3 D4Describe relevant standards and best practice in data engineering, analyse shortcomings and identify possible strategies and approaches to overcome them.
  • Examination
  • Lab assessment

Reading list

COMP60711 does not have a specified reading list.

Additional notes

Course unit materials

Links to course unit teaching materials can be found on the School of Computer Science website for current students.