Angelina Yang talks with Rain AI about speeding up data onboarding. Rain AI built a feature that uses AI to automatically infer what your data means, generate schemas, and write descriptions for tables and columns without manual work.
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If you don't have that, then the performance might not be as good as expected. I led my team, one of the principal engineers on my team, we build our techs to SQL two years ago and I've seen firsthand a lot of the pushbacks. One of the typical one is we didn't have a catalog. We know it's in our data team's brain. Like how does tables connect with other tables? And as you know, some of the companies as they grow, especially the data team, is short of resources all the time. How do you handle that?
At Rain AI, we have a very important feature that is called AI augmented the semantics. Many companies when they are onboarding Rain AI, they can just connect to their data source, upload a documentation of the data set and AI can just figure out the semantics for you and it will just generate like tens of thousands of columns and it will just make the schema with the descriptions and basically human. Just need to review whether it is interpret correct or you want to add more information in each columns, each table. We want to minimize the onboarding process.