Abstracts Computer Science

A framework for managing timetable data quality within the NMMU

by Dierdre Jean Els

This dissertation investigates the influencing factors on timetable quality, not only from a data quality perspective, but also from an information quality perspective which takes into account the quality of the business processes involved in creating the timetable. The Nelson Mandela Metropolitan University was used as a case study for assessing the quality of the timetable process, the quality of the source data, and the quality of the final timetable produced. A framework for managing the data quality during the timetabling process is proposed. The framework is based on reviews done on data quality management best practices and data quality aspects. Chapter 1 introduces the current Nelson Mandela Metropolitan University timetable, and motivates why data quality management is essential to its success. The scope and research objectives are presented for this dissertation. Chapter 2 covers a literature study on business process and data quality management best practices. The common thread through all the management methodologies investigated, was top management involvement and commitment to continuously improving the quality of data. Chapter 3 discusses various characteristics of data quality. Quality is determined to be whether the end result meets the quality requirements for which it was intended. Hence each system could have quality aspects that are unique to it. Chapter 4 explains various research designs and which were followed for this dissertation. The combination of literature studies, a questionnaire and a case study were used. Chapter 5 is a case study of the data quality and timetabling processes used at the Nelson Mandela Metropolitan University and is based on the research design described in chapter 4. The current business processes followed in setting up the current timetable are presented, as well as the proposed timetabling process that should produce a better quality timetable for the Nelson Mandela Metropolitan 4 University. The data quality aspects most pertinent to the Nelson Mandela Metropolitan University are determined, being timeliness, accountability, integrity and consistency, as well as the most probable causes for bad timetable quality, like uniform technology, processes, ownership and using a common terminology. Chapter 6 presents a framework for managing timetable data quality at the Nelson Mandela Metropolitan University using an Information Product Map approach that will ensure a better quality timetable. Future research is also proposed. It is evident from this dissertation that data quality of source data as well as the quality of the business process involved is essential for producing a timetable that satisfies the requirements for which it was intended. The management framework proposed for the Nelson Mandela Metropolitan University timetabling process can potentially be used at other institutions as well