文章基本信息

标题：Critical Data Consolidation in MDM to Develop the Unified Version of Truth
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作者：Dupinder Kaur ; Dilbag Singh
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2021
卷号：12
期号：12
DOI：10.14569/IJACSA.2021.0121242
语种：English
出版社：Science and Information Society (SAI)
摘要：Organization seeking growth and competitive lead should use Master Data Management (MDM) as a foundation for efficient decision making. An MDM framework creates a trusted and reliable continuous record of customers, products, suppliers and other shared data sets. In master data, the critical data is consolidated to portray essential business entities into a Unified version of Truth. To create trusted view of master data challenges like quality, identity resolution, analytics and investment are faced. In proposed research, a technique has been designed to generate Master Data to assist the policy maker to address the said issues. In this paper, four steps have been taken for master data creation namely: Data Enrichment, Data Matching, Data Merging and Data Governance. To achieve legitimate data quality TALEND open studio has been used for data pre-processing and enrichment. An algorithm is designed to match and merge the master records. To validate the designed approach, results are evaluated using Pandas Data Frame on Python platform. This paper will assist the policy makers of the organizations in formulating the business strategies.
关键词：Master data management (MDM); master record; TALEND; data matching and merging