You don't need to clean your data before using AIOps. The whole point is that AIOps can work with messy, siloed data across different teams and schemas, extracting insights without extensive preprocessing.
Chapters
When I was a kid, my mom, you know, we'd have the cleaning lady come and my mom would say, like, hey, the cleaning lady's coming. You have to clean the house first. So I was thinking like, but the cleaning lady's coming. Why do I have to clean my room? And you know, people often think something like that with AIOps. Hey, I have to clean up all my data before I feed it to AIOps so it can make sense of my data. And the answer is no. Part of the value prop of OPS is it can make sense of messy data, it can make sense of dirty data. And the fact that you have silo data and every team in your organization has a different kind of framework and schema, that's okay. Put the AI OPS layer on top of that and it can help make sense of that. So there's really not a lot of change you need to do to clean up your data before you bring AI. That's what AI. That's part of the value prop.