Improving Data Management for Better Itemization Process : Towards the High Quality Data in Product Data Management
Korpiniemi, Antti (2016)
Korpiniemi, Antti
Metropolia Ammattikorkeakoulu
2016
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-201605157888
https://urn.fi/URN:NBN:fi:amk-201605157888
Tiivistelmä
This Thesis focuses on improving data management for better itemization processes in the case company. Focus of the research is to identify and solve the root causes behind the problem why confirmed information in the product data management is not systematically received. This problem affects the processes where items are created and maintained and where there is a critical need for complete and high quality information.
The objective of this Thesis is thus to create an approach to improve the itemization process which would increase the quality of data in terms of component knowledge accuracy, reduce its delivery time, and would in the end increase competitiveness towards competitors. The study is conducted by, first, analyzing the current state of itemization process, combining the best existing knowledge, and creating an approach for information quality problem solving. This approach is then applied on an example case showing how to solving the data quality problem for the benefit of the case company.
The outcome of this Thesis is an approach for data quality problem solving. The approach consists of different methods based on: context, role, pattern, and aspect of data management that can be used together or individually to improve the received information quality, and a TDQM (the total data quality management) tool which can be used for continuous information quality improvement. The approach presents how to utilize the methods by showing the connections of high data quality dimensions between the methods.
The benefit of the research and created approach is that it can evoke questions and increase interest of the company to research their information quality and discover new methods how to improve the quality of data and the processes related to managing it. In the context of the case company, it could provide a more efficient itemization processes that would benefit the case organization and its stakeholders.
The objective of this Thesis is thus to create an approach to improve the itemization process which would increase the quality of data in terms of component knowledge accuracy, reduce its delivery time, and would in the end increase competitiveness towards competitors. The study is conducted by, first, analyzing the current state of itemization process, combining the best existing knowledge, and creating an approach for information quality problem solving. This approach is then applied on an example case showing how to solving the data quality problem for the benefit of the case company.
The outcome of this Thesis is an approach for data quality problem solving. The approach consists of different methods based on: context, role, pattern, and aspect of data management that can be used together or individually to improve the received information quality, and a TDQM (the total data quality management) tool which can be used for continuous information quality improvement. The approach presents how to utilize the methods by showing the connections of high data quality dimensions between the methods.
The benefit of the research and created approach is that it can evoke questions and increase interest of the company to research their information quality and discover new methods how to improve the quality of data and the processes related to managing it. In the context of the case company, it could provide a more efficient itemization processes that would benefit the case organization and its stakeholders.