Data Governance Model for Tagging Data Using Finger Printing


Authors : Deepa Mahadev; Asha K

Volume/Issue : Volume 6 - 2021, Issue 6 - June

Google Scholar : http://bitly.ws/9nMw

Scribd : https://bit.ly/2UOwbst

Data is considered as a raw entity which has impacted multidisciplinary research endeavors as well as government in developed and developing countries. Data is getting generated from a giant stock market to a tiny smart mobile phone. Hence, we are in the era of big data where data sets are characterized as Voluminous, variety, veracity, and Velocity. Today generating data from various sources is a matter of time and requirement. The data collected are easily analyzed through various intelligent models proposed by researchers based on the application requirements. Once data gets accumulated, one must take care of data governance, data ownership and data anonymity. With the advent in technology and growth of AI & ML, researchers did not concentrate on give back the analysis report to source of data generation point. Hence data governance, data ownership and data anonymity are all at their infancy. To this end, the paper aims to develop a data governance model which takes care of data ownership and tags data with source of availability. This is possible if data is finger-printed at the source of generation, thereby the ownership is confirmed, anonymity does not exist, and analysis report is back with the owner for improvement or modifying the existing system.

Keywords : Data Governance, Data Ownership, Data Anonimity, Privacy, Data Finger Printing.

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