Development of data governance components using DEMATEL and content analysis
- PDF / 816,823 Bytes
- 15 Pages / 439.37 x 666.142 pts Page_size
- 83 Downloads / 239 Views
Development of data governance components using DEMATEL and content analysis Kyoung‑ae Jang1 · Woo‑Je Kim1
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Organizations gain insight and derive value from data that drive their direction, and so data governance, which is a method of managing competitive data, is becoming more important. Researchers have recognized the importance of data governance and introduced various solutions, but the standards and scope of data governance vary, and integrated standards for data governance components need to be established. The purpose of this study is to define the concept of complex data governance and develop a framework for it by defining the data governance components. Using the decision-making trial and evaluation laboratory method and content analysis, we identified the data governance components and analyzed the influence of their relationships. Keywords Data governance · Data governance framework · Data quality · DEMATEL · Content analysis
1 Introduction Policy decisions in organizations are influenced by changes in the information environment, which has rapidly become a large data due to the development of broadband Internet, mobile devices, and social network services. The derivation of insight and value from data can provide a competitive advantage to organizations. Data governance is a data management concept concerning the capability that enables an organization to ensure that high data quality exists throughout the complete data lifecycle. The concept of governance and related terms were first introduced in Garvey’s book [1] who presented a new theory developed from a combination of market theory and an interest network. This theory later evolved into requirements embodied in data governance with the movement to recognize data as assets and * Woo‑Je Kim [email protected] 1
Department of Industrial Engineering, Seoul National University of Science and Technology, 232, Gongneung‑ro, Nowon‑gu, Seoul 01811, Republic of Korea
13
Vol.:(0123456789)
K. Jang, W.-J. Kim
derive value from them. It includes the people, processes, and technologies needed to manage and protect a company’s data assets to guarantee generally understandable, correct, complete, trustworthy, secure, and discoverable corporate data, and it is required to systemize organizations by connecting business processes with data. Data governance programs always affect the strategic, tactical, and operational levels in enterprises. To efficiently organize and use data in the context of the company and in coordination with other data projects, data governance programs must be treated as an ongoing, iterative process. Therefore, most companies have a need for data governance, and data governance components should be defined clearly to achieve its systematic introduction. Many researchers have recognized the importance of data governance and presented various solutions, although the views and scope are different. In addition, there have been many studies on data qu
Data Loading...
