Retention Plans and structured Data

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As you are thinking about how to manage your electronic records from network drives and your emails, you want to consider those structured database systems and how long you retain data, while you are looking at your overall strategies for retention of information.  Structured databases, in non-technical terms, are any type of system where data exists within a database that can be pieced together to create records, screen views, reports, etc.  Examples include accounting packages, human resources relational databases, customer relations management systems, or asset management databases, to name just a few common applications with structured databases.

Not properly managing structured data poses the same risks inherent in not managing emails or documents to an organization:  hefty costs associated with producing electronically stored information (ESI) during litigation (FOIA and PRA requests for governmental organizations) because that data must be searched and produced just as your records and emails.  There also is the business opportunity costs associated with not understanding (or leveraging) the information maintained within your business that could be useful/harmful.  And, when aging legacy systems are often maintained “just in case we need that data” there is a cost to keeping those systems running.  To get a copy of this article go to Retention Plans and Structured Data


EID – Electronic Document Management | Robert Blatt remove preview
Retention Plans and Structured Data
How does your organization manage retention plans requiring purging of information including structured data? You might answer that question by saying: What is structured data? I don’t know We just keep all our structured data Does your current retention plan apply to structured data?
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Robert Blatt, MIT, LIT, CHPA-III
Principal Consultant, Electronic Image Designers (EID).
AIIIM Fellow #175
Chair, Trustworthy Storage
Chair, Trustworthy Document Management & Assessment
Chair, ECM Implementation Guidelines
ISO Convenor: 18829, 18759, 22957, 18759)
US Delegate to ISO TC/171
TC/171 Liaison Officer to TC46 SC11
TC/171 Liaison Officer to TC/272



Absolutely agree with the assertion.  The issue with the structured repositories is still (somewhat surprisingly) being able to manage the retention and disposition of the data in any sort of automated way.  There really isn’t much out there in terms of solutions that can do this as the management solution (aka “the RM software”) needs a full entity relationship map plus access to either/both software or database system security to be able to lock down all the data elements across the tables for every single software that is identified as containing “records” data.  Given that structured DB systems tend to be used to record some sort of business “transaction”, that means just about ALL of them then.  And with large enterprise organizations often still having 1000 or more applications across their IT domain, that is a pretty daunting picture to take in!

Yes, I do know that some of the latest enterprise architecture tools have significantly improved abilities to query systems and dynamically build the maps, but, from what I’ve read, those capabilities are neither wholesale in their reach, nor unneedful of human validation for correctness.  One area where ML (Machine Learning) may actually earn it’s keep (without the need to put anyone out of a job)!

And that might be just the on-premise relational database-based systems.  When you start layering in massively shared cloud databases, data lakes and warehouses, Redis caches, data factories, fabrics like Microsoft’s Common Data Service (and, and, and….), accessed through identity and directory providers like Azure Active Directory, containerized and serverless applications, Graph databases (a whole different kind of beastly hell!), and so on, and so on, even a very committed organization seems likely to throw up their hands in resignation��.

I haven’t heard of any workable, economically viable, solutions to this.  Wondering if you have (as I know from our past conversations you have a very broad knowledge base)?



Hi Robert,

Thank you for sharing. This is something that I am quite interested in, as we just developed and implemented a new retention rule in our structured ERP database for the first time, and have a lot of other data that we would like to clean up (and keep clean) going forward. I clicked on the link that you provided and it took me to a 6 paragraph or so post on the topic. Is there a more in-depth article available? If so, how do I access it?


Ashley Haughton
Records and Information Manager
University of Lethbridge


Smart GDPR

Thomas Pereira Antunes
Center of Competence Records Management
AXA Switzerland


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