 Live from Las Vegas, it's theCUBE. Covering Splunk.conf 19, brought to you by Splunk. Okay, welcome back everyone. Live in Las Vegas, we're here for Splunks.conf. I'm John Furrier with theCUBE. This is our seventh year covering .conf, but .conf's 10th year of their end user conference, their customer conference. I've been excited to watch the evolution of Splunk and a lot of it's because of their great products. And we have our next guest for you, Fayyapeng, Senior Director of Product Line Management for Splunk, Business Flow. Welcome to theCUBE. Hi John, thank you so much. Thanks for having me. Well, I'm glad to have you. One of the successes of Splunk has been great products. They never deviate off the core, kept building on it. You're in the Senior Director of the Product Line for business flows, analytics. All I see everywhere is dashboards and visualizations. It looks so easy. Tell us about what your products are doing. Yeah, definitely. And I think one of the places to start is just how we moved into this area and started the new product. A lot of people know us for IT and security use cases, but a lot of our customers are also using it to address business needs. So what they really saw was the value of Splunk to pull data from across different silos. So in a business sense, it could be, I have different systems for maybe my leads, sales, and closing the books, right? Those are all disparate. It's really hard to pull it together. And so they came to us saying, we'd love a way to stitch this together and be able to visualize it. And that was really where Splunk Business Flow was born from. So we actually simplify it by connecting all these disparate data points, creating a full journey view or process view that you can graphically see what's happening, and then point and click and drill in. So it's really opening up a whole new set of users for us with that, and a whole new set of use cases that way. So you guys are almost building a new abstraction around a holistic view of the data. Is that kind of what, am I getting it right? Conceptually, yes. So if you think about, we have tons of data, it's tons of events. If you know a common thread, like a user, and how they might go to the store and then do something online, and really understand the customer experience, if you could actually thread that all together, we would know so much more about their customer experience, and that's what we're able to do, and we do it seamlessly for the customer. Well the database guy in me from the old 80s college saying, hmm, I got to write a schema for that, I got to store the data. I mean, in the old way, it was really hard. It was hard. Exactly. I mean, compare the pain or even capability. You're hitting exactly the pain point, right? That's why it's been so hard to do that because it was so rigid. The beauty of Splunk is the schema and read aspect of it. So because we store all the data and then we can distract it as needed, we do the search on demand, and that's how we're able to actually stitch it together. You know, Faye, one of the things that I've been saying about to our audience around why this conference is relevant this year, and in the industry is that data is now like code, and it needs to be addressable. And also there's a lot of contextual issues around knowing what data is needed when and where, when to throw it away. Some data's not worth hanging around. So this is a real kind of programmatic issue. This has been, this is a big story. Yeah, yeah. And I think like one of the things has been the struggle of, well, people have made a lot of probably more conservative decisions earlier on in their data, and that's why they weren't able to get the information. And so the main pain point we always heard was, I got one piece of data, but now that I look into it, crap, I need to know what else there is, and then it's another three-week cycle, right, to pull that data in, bring it all in. Well, now that's all in Splunk, you can just pull it as you need it on search, on demand. It's a use case that from an operation standpoint, they're pretty comfortable with handling Splunk. They know what it means to Splunk the data. Exactly, and we really see as a partnership between the Splunk admin as well as the business users, the Splunk admin helps to get it all set up, and then the business user can actually investigate on their own, and they don't need to know SPL or anything like that to be able to use the product. Talk about the business flow constant again. I want to kind of understand that from a product standpoint. Is it a part of enterprise suite? Is it part of, how do people use it or buy it? Exactly, that's a great question. So it's a premium solution, so you do need Splunk Enterprise or Splunk Cloud, and then this stacks essentially on top of it. And so it uses the underlying Splunk data, but then it's also doing the additional work of doing the correlation across it, stitching it together, providing the visualizations, and then from there you can do things like A-B comparison mode, you can see conversion rates, you can drill down all the way into the actual event. So the beauty of it is being able to see the holistic picture, but then go down into the individual event and journey. We hear a lot of the target audience being the business analyst or the security analyst. For your products, who is the target customer? It's definitely the business analyst, and I think there is some crossover with IT and security as well. So we actually had a session here where our own IT, internal IT, you spoke business flow to monitor their ticketing system and look for black hole tickets. So I don't know if you've ever submitted an IT ticket and you never hear anything back because it's gotten lost. We don't have an IT department. But yeah. We're all born in the clouds. Exactly. But one of those... We're lucky. Exactly, you're very fortunate. But it was one of those problems where you hear a lot of IT departments. You know, you might have, because you're outsourcing certain persons, you lose some of those tickets and you don't know what happened. So they were actually able to use the product to see that. But it also applies to people within one example. We have, sorry, I'm thinking of some public customers that we have. So Domino's is a public customer that was a beta customer that used it for payment processing on Super Bowl. So that's another great example. Yeah, and obviously scale is huge here with the data. So I got to ask the cloud question since we brought up cloud. Is this service cloud enabled in the sense of is it an on-premise thing or does the cloud workflow kick into the analytics? How does the cloud play into all this? Yes, so it sits on top of both. So it works either with the Splunk Enterprise or Splunk Cloud Enterprise License essentially. And then the actual architecture of it is a hybrid environment. So we have a hybrid component that's in our own hosted cloud that feeds the UI. And the great thing about that is that we're able to update the product very quickly and push updates to the customers very easily that way. Take us through the history. What's the origination story behind this product? Was it a reaction to customers kind of tinkering around with it? Was it requested? Was it a feature? Was it an idea that came out of an existing thing? And how long has it been in the motions for? So we first announced it back in May of this year and have added additional functionality as part of COV. And it did come out of customers and them seeing the opportunity with the machine data. So there are a lot of great stories that we've had historically. I think to buy airports, you can see some different stories before people piece the journey together. And so out of those conversations, the idea was born. Every product line has a list that didn't make the cut on the product. It's called the roadmap. It's also new things. What are some of the things that you see, big picture areas that you're going to focus in on to extend out the capabilities and value of the product? We really see the product evolving the same way that you see a lot of the portfolio overall. So Doug has talked a lot about investigate, monitoring, analyzing and act, right? And so those same concepts apply into how you think about a process as well. So right now we're really helping the investigation and monitoring, but we'll also continue to extend across that spectrum with time. A lot of cloud services, microservices, observability, a big part of all this. Yeah, definitely in how we've built the product, but also I think it can sit alongside some of the other things that you're also seeing in that realm. Final question for you, for people that are watching that couldn't make the conference, what's the biggest story here for .conf this year? How would you describe it? Overall I really think it is our data to everything message that we're discussing. I think today you can really see how we apply in all these vast areas and really the power of being able to have access and make that data actionable and do something with it. Thank you so much for coming in and sharing your insights here in theCUBE. Appreciate it. Thank you so much. It was so nice to be with you today. I'm John Furrier here in theCUBE coverage here in Las Vegas with .conf, Splunk's annual conference it's their 10th year. Our seventh year covering them. We'll be right back with more day two coverage after this short break.