VIDEO: Why Move Your Data Repositories to Graphs?

Jul 19, 2019


Infoloom Inc. CLO Michael Biezulnski makes the case for migrating your data repositories to graphs (not graphics) in this clip from his presentation at Digital Experience 2019.

Watch Michael Biezunski's complete Digital Experience Conference presentation, A204. Moving to a New Home Once it Gets Messy, in the Digital Experience Conference Video Portal.

Transcript

Michael Biezunski: Why switch to graphs? Well, first, it's a hospitable environment for multiple dynamic repositories to co-exist. So if you're interested in integration, graphs are a good way to go because you can integrate any database structure, XML structure, I mean, you basically are free to decide how you want a graph to exist.

You can also, as I've shown before, create new inference rules to validate data on your graph depending on the conditions, you know, the neighboring values, or the values of the neighboring, neighbor links. And it's also maintainable over the long-term because a graph can have areas that are messy without breaking the rest. So here I just fixed one point on my graph but obviously there may be plenty of other areas which need to be clean.

But I'm not doing that right now, I'm just doing one at a time here. And here also I have, I mean I've been working with the IRS for a long time to provide a part of their website called Tax Map which is a topic map of their forms, publications, and other, you know, information that they publish. And one of the problems with IRS information is that, I would say, it's messy by design. There's nothing rational about the tax law. It's just a result of who is asking for what, and they got it and it's in the tax law. So I mean, don't try to have a comprehensive view of the tax law that makes sense because it doesn't exist.

Nevertheless, it's important for them to be able to show what they have without, and that's really important, without simplifying it. So they try three times to build taxonomies. Like hierarchical taxonomy of concept and sub-concept and sub-concept. It didn't work. It didn't work because either the experts did not agree, or they had new things coming up that didn't fit, and it was just too complicated.

At the end. the results were not what they expected anyway because things were put in a box which was not the right one and it was many boxes at the same time, so it didn't work. But the topic map, which was an adaptive way of getting information automatically out of their sources, had some parts that were cleaned by hand. Most of it was still messy, but it still worked.


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