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Department of Computer Science

Specifying and Optimising Data Wrangling Tasks

Primary supervisor

Additional information

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Other projects with the same supervisor


  • Self-Funded Students Only

If you have the correct qualifications and access to your own funding, either from your home country or your own finances, your application to work with this supervisor will be considered.

Project description

Data wrangling is "the process of cleaning, structuring and enriching raw data into a desired format for better decision making in less time" [2].

To clean the data prior to analytical tasks, a wide variety of data quality techniques and tools are used [1]. There is also a trade-off between flexibility, performance and usability of data quality techniques and tools [1]. Highly flexible tools tend to overburden the end user with the need to complex application programming interfaces towards expressing quality-aware manipulations over the data. The balance lies somewhere in a spectrum between highly flexible and extensible solutions and less flexible but efficient and user-friendly frameworks. In practice, a combination of complementary tools and techniques may be needed in a data quality management project.

This PhD project aims to investigate popular techniques and tools used by data scientists to conduct data wrangling tasks prior to big data analytics and develop domain specific methods and languages.

Person specification

For information


Applicants will be required to evidence the following skills and qualifications.

  • You must be capable of performing at a very high level.
  • You must have a self-driven interest in uncovering and solving unknown problems and be able to work hard and creatively without constant supervision.


Applicants will be required to evidence the following skills and qualifications.

  • You will have good time management.
  • You will possess determination (which is often more important than qualifications) although you'll need a good amount of both.


Applicants will be required to address the following.

  • Comment on your transcript/predicted degree marks, outlining both strong and weak points.
  • Discuss your final year Undergraduate project work - and if appropriate your MSc project work.
  • How well does your previous study prepare you for undertaking Postgraduate Research?
  • Why do you believe you are suitable for doing Postgraduate Research?