Abstract: 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.

Dupinder Kaur and Dilbag Singh, “Critical Data Consolidation in MDM to Develop the Unified Version of Truth” International Journal of Advanced Computer Science and Applications(IJACSA), 12(12), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0121242

@article{Kaur2021,
title = {Critical Data Consolidation in MDM to Develop the Unified Version of Truth},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0121242},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0121242},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {12},
author = {Dupinder Kaur and Dilbag Singh}
}