>> Announcer: Live from Orlando, Florida, it's theCUBE, covering .conf 18. Brought to you by Splunk. >> Hello everybody. Welcome back to Splunk's .conf 18, #splunkconf18. You're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante. He's Stu Miniman, @stu, @dvellante. Tweet us with any questions you might have. Larry Shatzer is here. He's an Operational Intelligence Engineer at Myriad Genetics and he's joined by Amarbir Dhindsa who's an Analyst in SalesOps, also at Myriad Genetics. Gentlemen, welcome to theCUBE. Good to see you again. >> Thanks for having us. >> Thanks for having us. >> Myriad Genetics, tell us about the company. What do you guys do? >> So we test people to know if they have a tendency to develop, maybe breast cancer, ovarian cancer. We have a series of questions that people like to ask of like, will I get cancer, do I have cancer, what should I treat it with, and how should I treat it? And so we try to answer those questions over different diseases and cancer being the most prevalent one. >> And Operational Intelligence Engineer, what does that entail? >> So I'm part of the group of developers that maintain the labs and I work in the Business Intelligence group and then my primary focus is the lab and the operation. So I work with the different process engineers and clinical scientists to help maintain their, the different ask days that they perform and make sure that the robots are working at peak performance and if we could predict where problems might be. >> And Amarbir, you used to be in operational intelligence, right now you're in the sales side in the line of business, is that right? >> Yes, yeah, yeah. I get to mix both worlds and look at some lab metrics and see what kind of effect they're having on business indicators like turnaround time. So if there's something weird going on in the lab, we want to see what it's effecting in terms of the turnaround time that we might be getting customers back their sample in time, or if it's taking longer than competitors, or if it's taking a little bit longer than the norm. >> Now, in the old days of business intelligence, you had maybe a guy, maybe a couple of folks, maybe a team of people, but they were the experts, and you'd go there and you'd beg them to build theCUBE. And then you'd wait. And then by the time you got the data, often times things had changed. You got a nice report but sometimes it just wasn't worth it. You probably remember that world. >> Yes. >> How is that dynamic changed? >> Users are more demanding. There's a lot of more users that are more savvy when it comes to technology. A lot of our users were used to doing things in Excel that I was surprised that they even knew what a VLOOKUP was. And stuff like that. And their level of quality that they expect from you is higher but they also know their data more than you know it. There's only so much data I can understand, you know. We've got all kinds of parts of the domain knowledge that's needed to perform different parts of the process. You know, coming from the chemistry stuff to sales, to HR, to finance, all that stuff, you lose focus, and you go from one project to another and it's hard, so now it's a better world where the users come to you also with solutions in hand. Sometimes that's bad, but sometimes it's good. >> Well, but so the tooling has to change to accommodate that right? >> Larry: Yes. >> So presumably that's where Splunk fits in but how has the tooling evolved? And I'm really interested in learning how you've become this, sort of, power user within sales presumably. >> Yeah and I can attest to both worlds. So before I moved into sales, I used to monitor quality and labs manually. So everyday I'd come in and a good hour, two hour would be spent characterizing each platform, each re-agent, each user, and now it's just one click away. So you can get a verdict on quality daily, really quick and you can make changes really quick, rather than something infiltrating the system, having its effect and going out, you can catch it way early. And my days have gotten a lot more productive, right. Instead of copying and pasting from a remote query, now that query runs in the background and populates everything. >> So where does Splunk fit in all this? How do you use it? >> So we started with Splunk with the traditional use case of we've got a web service that we've deployed, we want to bring in the logs and analyze them, and then we were in a meeting with some business users and we happened to show them Splunk and one of the users was like, I want that. We've got logs coming off of our robots in the lab that when users click this button that they shouldn't click that we can't change 'cause it's from a vendor, we want to know when that happens, because there's a potential for something bad happening down stream. So we want to catch that early. And we've got these Perl scripts that are ugly, hard to maintain, can we look at Splunk? And so we were like, okay we'll start looking at your logs. It's more data, I'm a data nerd. I like looking at random weird data. So we started bringing it in and then it just exploded from there. >> It's actually been the catalyst for change right. Splunk has been the catalyst for change, where we've gone from manual oversight to having an automated oversight. Not just in the lab end but also in the front end of where samples are coming from, where volumes might be decreasing. Is there a special market where there's a downtrend that we want to be conscious of, not at every weekday of reporting in a row. We want to be conscious of that everyday. It's hard to find that manually and Splunk is the catalyst that's given us real time information on key performance indicators that we can act on. >> One of the things I'm wondering if you can comment on is how much are you the one that everyone goes to? You're the center of knowledge, all the data lives there, and how much does this tooling enable you to allow the business team, the sales team, to be able to self-service? You've given them a dashboard and they don't need to come to you. >> It's been a long journey and getting to that point I hold weekly user sessions with different users to sort of help enable them, hold their hands. At the early on, it was, this is how you do a search, this is what alert is, this is what a dashboard is and now it's more about what are the problems you're having and then showing them different dashboards that use different techniques that I'm like, this is for this user, but you can apply some of the same techniques and then they'll just copy, paste, and change it for their use case. And it's just been fantastic to enable them. Since our group is small, there's me and another guy, who's here, wandering around right now. Our mantra is teach them to fish. You know, they know their data better than we know it. We prefer to be more like a consultant with them to say we know the math, we know the techniques, you know the data, let's just put our minds together, then usually will come out with a great product at the end. >> So one of the things we were talking about was how Splunk is different than some of the other disruptive technologies and you're able to do things that you really couldn't do before. Like you can't teach lines of business users how to maintain Perl scripts. It's just not going to happen right. And so now maybe in SecOps we heard that some of the sim tools were competitive and Splunk was disruptive 'cause it was easy to use but it seems like, as Amarbir was saying, this is a catalyst for change because it's new, it's different, it's enabling you to do things that you really couldn't do before. Is that an accurate characterization? >> I think that is. The other aspect, at least for us, is that some of our business units were so data starved, because they just didn't have access to the data. Armabir's old boss, when he worked in the lab, said if you don't have answers to your questions, it's your own fault for not asking for help. Now he's like, now with Splunk in the mix, we've gained insight to some of our products that we've had running for like 13 years with no visibility into it and now we've got this visibility and they're discovering new and interesting metrics that they want to look at and make decisions off of. >> Yeah I'm wondering, we've heard from a number of customers where they've got really what we'd called those hero stats out there, you know, we heard one company up on stage this morning was like, oh saving $60,000 a month in fraud. I'm curious as you report to the business, what success to your team? >> Well we've been able to identify turnaround time changes really quickly. We've reduced it by an appreciable amount when problems come in. That's the cool thing about Splunk. You can actually catch things before they infiltrate your system. Now you were talking about it might be a little bit harder to get users to be comfortable with the search processing language but one of the keynotes, somebody was saying that if you know about 20 commands in Splunk, and you're comfortable, three users sessions that Larry runs, you can explore your data a little bit more and you can become a steward of your data, that will help you catch influxes of problems way before they become prevalent. >> So you're saying they can do some basic SPL in there, it's not just okay, we've got a gooey in a dashboard for ya. >> I think with a little bit of help they can right. Especially with the documentation and the videos that Splunk provides, users can be self proficient to some degree. >> Where are you today with Splunk? I mean how do you measure the size of your Splunk installation? Is it capacity ingested? Or number of indexers? How do you guys look at that? >> We're a small license. We'd only ingest about 20 gigs. Or that's what our license is. And we do about half of that, so we make that license count. We are also very pragmatic, starting off with, what do we want to ingest first? What's the highest value logs that we can get in that we could, with a little bit of effort, get the most reward out of? And then it's just been growing. And also as our company's bot and a few other companies as we've made some acquisitions, some of them are like, we want some of that as well. Some of them run the same platforms we do in their lab, both labs, so we can take what we've learned there and apply it at other places as well. >> How long you been a Splunk customer? >> Larry: Five years. >> So it's been a while though. Okay so you're likely going to stay more focused but it was interesting, 'cause Amarbir you go from an operations intelligence role into a sales role, that's sort of, an indication, that this platform is permeating throughout the business but will that continue or you pretty much confined to where you are and you're getting the value out of what you have today? >> There's new users asking us questions all the time. In fact, just yesterday got an email from a user in a different lab that we haven't been focusing on, saying hey, in fact it was Amarbir that was talking to him, saying you should send an email to Larry and his boss and ask about getting some more visibility in your lab, you know, their small little lab that runs, you know, they're not the big product that we offer but they've got data needs. Just because you don't impact the top line like other parts of the business, doesn't mean you can't have data problems and data needs yourself so. >> I think once people see the answers that Splunk can provide in their realm. So for a given lab, if Splunk can answer your questions and you're immediate needs in a quick fashion, then you become enamored and want more, as to what Splunk can provide. And it's done that across a variety of departments in our company and more departments, I think, will hop on board when they become more familiar with what Splunk can do and how fast it can do it. >> And you're in the sales organization correct? >> Right I migrated over into the sales organization and over there, we're really concerned with what the effectiveness of our sales call is, right. So now we can, kind of, the world is the possibility with Splunk. If we have data, now we can explore it. In that past, the exploration wasn't as user friendly and I know user friendly is one of those things that people don't associate with the SPL, kind of based platform, but I think once users see what this can do, they're a big fan of it. >> I mean I ask because you're not marching to the tune of a centralized analytics group. The sales folks can say, hey I need this, help me. And on a moment's notice. And so you're a resource that's dedicated for them. How do you like that world? >> It's a little bit of a change but it's data rich, so I kind of love it. And all of a sudden, we can model things. I'm just going to give you a quick example. We can model a territory that overtime has changed from being a poor performer to being a good performer. Now we can try and get indicators that have changed overtime and we can monitor them and maybe propose changes to area managers that can emulate that process. So that's just one use case where data will drive decisions and possibly can give more insight to decision makers. >> All right guys we got to leave it there. Thanks so much for coming to theCUBE. Always appreciate the customer insights and congratulations on your great work. >> Thank you. >> Thank you very much. Thanks for having us. >> You're welcome. All right, keep it right there everybody. Stu and I will be back with our next guest. We're live, day two from .conf 18. You're watching theCUBE.