Personalized Data Set for Analysis

TL;DR

This paper proposes a new service layer within data management architectures to enhance privacy and compliance when sharing large organizational data sets for analysis and testing.

Contribution

It introduces a novel data governance service layer designed to preserve privacy and ensure regulatory compliance in organizational data sharing.

Findings

Enhanced privacy preservation in data sharing

Improved compliance with data regulations

Framework supports secure outsourcing of data

Abstract

Data Management portfolio within an organization has seen an upsurge in initiatives for compliance, security, repurposing and storage within and outside the organization. When such initiatives are being put to practice care must be taken while granting access to data repositories for analysis and mining activities. Also, initiatives such as Master Data Management, cloud computing and self service business intelligence have raised concerns in the arena of regulatory compliance and data privacy, especially when a large data set of an organization are being outsourced for testing, consolidation and data management. Here, an approach is presented where a new service layer is introduced, by data governance group, in the architecture for data management and can be used for preserving privacy of sensitive information.