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Michael Cesino

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The Foundation of Enterprise Data Management and Data Governance

Posted by Michael Cesino on May 21, 2020 2:52:00 PM

Greetings!

 

I hope that this email finds you well.

 

I'd like to share a good article on modern data modeling, why it's important, and how it can help your organization. The abstract and a link to it are below.

 

ABSTRACT: Data modeling has expanded to support data management, data governance and data intelligence. Managing the metadata is the key to managing, governing, and cultivating the intelligence from the design. The article does a good job explaining the reasons why it is difficult to manage what you can't see, or to make good decisions from lack of visibility. The needed visualization for the design is provided through data models which in turn create the metadata to standardize the data design across the enterprise.

Modern Data Modeling the Foundation of Enterprise Data Management and Data Governance

If you have any comments or thoughts, we would love to hear from you.

Sincerely yours,

Michael Cesino

7 Ways Data Modeling Is Critical to Managing Data Privacy and Governance.

Posted by Michael Cesino on Jan 10, 2020 9:28:30 AM

Visible Systems Corporation recent data governance solution is designed to govern data in accordance with the most recent data privacy and security regulations (updated 4/19/2021).

The Visible Data Governance edition is now available for you to ascertain and comply with the critical underpinnings of data governance.

Visible Data Governance  (Click here to view the PDF) includes these features:

Upon Design ...
  1. Readily examine all representations of sensitive data in your enterprise architecture, system design, system architecture and configuration documentation; change control records; other relevant documents or records.
  2. Find out who the personnel are responsible for establishing the systems; personnel with responsibilities for updating the systems; and personnel with information security responsibilities for systems and networks.
  3. Reuse various design time components, work product, including native to cut down on the amount of time in developing data governance processes
  4. Organize processes for managing baseline configurations; for developing and documenting an inventory of system components; and for updating inventory of system components.

Upon Implementation ...

  1. Apply personal and sensitive data recognition techniques so you are better able to control user experiences.
  2. Support model and data integration from major databases to work effectively across platforms. Contains a query analysis to enforce differential privacy for general-purpose SQL queries - embedding a differential privacy mechanism in the query directly; the transformed query enforces differential privacy on its results and can be executed on any standard SQL database.
  3. Manage the privacy data life cycle from collection through storage, analysis, transfer and disposition.

    Click on Privacy Data Life Cycle image below for more details and recorded demos.
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