Data Quality Management Tool for Service Management Platform

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Journal Title
Journal ISSN
Volume Title
Perustieteiden korkeakoulu | Master's thesis
Date
2022-07-29
Department
Major/Subject
Computer Science
Mcode
SCI3042
Degree programme
Master’s Programme in Computer, Communication and Information Sciences
Language
en
Pages
64+6
Series
Abstract
Data is a crucial element in every information system and software application. Data quality concerns are not limited to Information Technology (IT) but involve various science realms. The growth of data is not a new phenomenon, “big data,” “data asset,” “data-driven business,” “data warehouses,” and “data lakes” are accepted as common terminologies. The value from data can only be harnessed if it meets specific standards and has the required characteristics. The investment in artificial intelligence, machine learning, and automation will go in vain if there are no data quality checks in place. Data quality management has long been studied in various fields. The studies have produced several frameworks and methodologies to work with data quality management. However, the service management domain of service science discipline, particularly IT Service Management (ITSM), has been challenged by data quality issues in recent years. The ITSM implementation is facilitated and driven by platforms, such as ServiceNow. The capabilities of ServiceNow expand beyond the conventional ITSM platform. It aims to address IT concerns and service management of enterprises. The thesis discusses and elaborates on data quality problems found in ServiceNow, an enterprise service management platform. It touches on available and applied solutions, then presents a pragmatic solution developed to address any data quality issues. It provides extensive details on the design and development of the tool, which forms a central part of the solution. Finally, concrete evaluations are presented using practical and real-world cases.
Description
Supervisor
Vuorimaa, Petri
Thesis advisor
Juola, Mikko
Keywords
data quality, information quality, data quality management, data modelling
Other note
Citation