Data Governance predictions from Forrester
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A clip from Atlan's October 2023 masterclass with Forrester. Raluca Alexandru explains why data governance moved from a nice-to-have to a core function as AI applications arrived, and why she expects AI governance questions to grow once models reach production.
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- Raluca AlexandruAnalystForrester
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Raluca Alexandru
0:00 I picked up some of the predictions that we did for this year, because the predictions at Forrester for 2024, I think they're coming up in a few days, so keep an eye on those. But I just wanted to mention these ones because I think they were quite accurate, and I'm not gonna talk about the numbers because we do the evaluation of this a little bit later. But for this year, just to understand the present to sort of be able to predict the future, as it was mentioned by Austin and Swami earlier, I think there's been a huge increase in...
0:26 And we've seen that with a lot of the companies that we talked to in organiz— There's been a huge increase in organizations trying to formalize and give some more shape to their data governance programs, and that comes as a need. Well, i-i-it's not a nice to have anymore, but it's a core functionality that organizations are building on and trying to understand how they can be on top of the data, especially with the, with the upcoming applications of AI and all the conversation about, you know, whatever goes in, that's the quality of our output.
0:55 So there is a huge interest and big investments, I would say, in this area to actually bring data governance programs to the more mature level. And the other one that I wanted to highlight here, because you can see it on the screen, you can read it, is that the prediction was, at the beginning of the year, that one in four techs will report to their board on AI governance, which is a very important topic nowadays, and there's a lot of questions flying around. I think none... Well, not all of them have been asked yet.
1:22 There's gonna be quite a bit coming up beginning of next year when people actually get to the point where the models are in place and the results are starting to come in, and they're wondering how to actually manage that and how to govern the data that is coming of all the, out of all the AI applications that are coming up in the, in this space.
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