Building a modern data registry: Go beyond data classification – Help Net Security

Help Net security

The focus of the article is privacy, particularly meeting privacy requirements to keep people’s data safe.  With privacy regulations being introduced globally there seems to be a surge in urgency to comply with the new laws.  A delicate balance must be met when an organization decides to become data driven while ensuring data privacy.  It seems that the current tools for data classification and cataloging are not able to fulfill the need to find, map and inventory data assets accurately and efficiently.

Building a functional and operational data registry
A possible solution might be to create a data registry that can list what data is kept, where and why. An organization should build the registry in an index-like map that focuses on five key functionality and operational characteristics:
Content granularity,
Usage context
Data source coverage
Ability to scale
Dynamic not static

Creating a full accounting and inventory of your enterprise’s data assets A hybrid approach to content discovery and contextualization can be achieved by considering four key requirements:
Entity discovery and resolution
Entry correlation and contextualization
Entity classification by type and category
Metadata capture and cataloging

An organization needs to be able to account for what data they hold and who the data belongs to.  The modern data registry looks beyond simply classifying and cataloging data to show the correlation and association of data to a data subject.  Understanding the connectedness of data to high-value identities no matter if they are located in the data center or the cloud is crucial for establishing and aligning the organization to meet the privacy regulations.

Access to link:

Heyrling Oropeza / Spring 2019/ INFO 653-01

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Posted in Classification, Knowledge Structures, Preservation, Uncategorized

by Hugh McLeod

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Pratt Institute School of Information
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