“Without data, there’s no great AI, says Amit Walia, President, Products & Marketing at Informatica. “Now that AI is really becoming pervasive and at scale, you really need to give it relevant good contextual data. We see that happening a lot in the world of enterprise. Finally, enterprise is arriving at the point where they want to use AI for B2B use cases, not just consumer use cases that we are used to. AI is a part of everything that we do in data.”
Without Data There is No Great AI
The language that AI needs or speaks is data. Without data, there’s no great AI. This is something that we’ve known all this while, but now that AI is really becoming pervasive and at scale, you really need to give it relevant good contextual data. We see that happening a lot in the world of enterprise. Finally, enterprise is arriving at the point where they want to use AI for B2B use cases, not just consumer use cases that we are used to. AI is a part of everything that we do in data.
It has really helped to improve productivity and automate mundane tasks. There’s a massive skills gap and I think you look around the economy is fully saturated with jobs. There is still so much work to be done with more data and different data. AI is helping make some of those mundane activities become a lot easier and autonomous.
Data is Becoming a Platform of Its Own
Our data scientists have gone from heroes to superheroes. Think about it. What we are seeing in this world is that data is becoming a platform of its own. It is getting decoupled from the databases, from the applications, and from the infrastructure. To truly be able to leverage AI and build applications on top you cannot let it be siloed and be held hostage to its individual infrastructure components. We’ve seen that fundamental change happening where data as a platform is coming along.
In that context, the catalog becomes a very pivotal start because you want to get a fuller view of everything. You’re not going to be able to move all of your data to one place. It’s impossible. But understanding that metadata is where enterprises are going and then from there you can have a customer experience journey with MDM. You can also have an analytics journey in the cloud with an AWS or an Azure. You can have complete governance and security and privacy journey while understanding anomalous activity.
Metadata Is the New OS
Data is everywhere. It’s like the blood flowing through your body. You’re not going to get all the data in one place to do any kind of analytics. You’re going to let it be there. We say that metadata is the new OS. Bring the metadata, which is data about the data in one place, and from there let AI run on it. What we think about AI is this; LinkedIn is a beautiful place where they leverage the machine learning algorithm to create a social graph about you and me. If I’m connected to John I know now that I can be connected with you. The same thing can happen to the data layer.
When I’m doing analytics and I’m basically searching for some report, through that same machine learning algorithm at the catalog level now we can tell you that this is another table or another report or another user and so on. We can give you help back ratings within that environment for you to do what I call analytics on your fingertips at enterprise scale. That’s an extremely powerful use case of taking analytics, which is the most commonly done activity in an enterprise and make it accurate at enterprise scale.