>>live from Las Vegas. It's the Cube covering Splunk dot com. 19. Brought to you by spunk >>Welcome back, everyone to keep live coverage here in Las Vegas for Splunk dot com. 10th anniversary. 10 years of doing their big customer shows. Cubes. Seventh year of covering Splunk I'm John Ferrier, Host Cube. Our next guest is Cube. Alumni seem Haji, senior director and head of platform on industry for Splunk Knows the business way last topped. 2014 Great to see you. >>Good to see you again, John. You've been busy. I have. It's been a busy time. It's Plunk. >>You have been in the data business. We've been following your career for the years. Data stacks now Splunk on other endeavors. But you've been in the data, even swim in the data business. You've seen clouds scale, you understand. Open source. You understand kind of big dynamics. Splunk has a full enabling data platform. Started out with logs keeps moving along the by companies that interview. But this'll platform concept of enabling value valued customers has been a big part of the success that it continues to yield success every year. When people say no, what is successful data playful because everyone wants to own the data layer because we just want to get value on the data. So what as a product market, our product person, what is the date of platform? >>So it's really a question and, you know, you gonna hit the nail on the head when you said we've been talking about the data platform for several years, like decades. Almost so if you think about, you know, data platform, like, way back when and I'm dating myself. When I graduated from college, you know, people were looking for insights right there. Like give me a report, give me a dashboard way. Went into data, databases of data, warehouses. Enabling this you actually think about the data platform or data to everything. Platform is, as we explore. Call it. It has five critical elements in my in my mind. You know, the first is how do you get all of your information? Like the data that's coming in from networks, logs, applications, people, you and I generate a ton of data. How do we get this all together into a single place so you can get insights on it? 1 may think that it's pretty easy, but the truth is, we've been struggling as an industry with for decades. So it's fun to think what super unique is you can actually bring in any of the data. And some of the challenges that customers have had in the past is way forced them to structure this state of before they can ask questions of it. What's wrong? It's free form. You can bring it in any information and then structured when you're ready to ask that question. So you know a data platform. Number one is flexibility in the way you bring your data second. And you know this being the business is getting real time insights, alerts on your phone, real time decision ing and then you have, you know, operating in different ways on cloud on premises, hybrid environments. That's the third. And I think the fourth and the fifth are probably the most important, and into related is allowing like a good data platform caters to everyone in the or so from your most non technical business user to the most technical data admin I t. Guy security analysts with giving them the same information but allowing them to view it in many different ways and ask different questions of it. So we call this, you know, explained is from a product marketing in a business standpoint way Refer to it as many lenses on your same data. Good data platforms do that while allowing an empowering different users. So those are the five in my >>love kicking out on platform converses. Second, we could talk for now, but I know you got busy. I want to ask you all successful platforms in this modern era of rocket texture. When you get cloud scale, massive data volumes coming in need key building blocks. Take me through your view on why Splunk been successful plateau because you got a naval value from the dorm room to the boardroom. So we've gotta have that use case breath what you do. What key building blocks of this point. Data platform. >>Great question. And, you know, we've we've kind of figured this out is a cz. Well, a cz have been working on building out these building blocks at a most critical customers, right? Did you think about it? You start with the core, the index, if you will. And that's your place to bring you know, slung started with all your logs together and it's your single go to place then, as you think about it, with working with customers, they need massive date engines. So what we just announced today the general availability of data stream processor and data fabric search. It allows you to have those two massive engines from How do I bring my streaming data in to have Can I do massive scale processing? Thea other elements around a machine learning right. So in a world where we're moving to automation, that's super critical to the success. And then you have consuming the way you consume insights or uses consuming sites. If you think about you and I and this amount of time we spend on our phone, how do we make it easy for people to act on their information to those your core platform building blocks give index. You have your date engines, you have a I am l. You have your business analytics and then you have your portfolios on top, which is use case specific, if you will. For I t for security and then for de mops. >>That's awesome. And let's get into the news you were your product. Kino today? Yes, they was opening day. But I want to read the headline from Lung press release and commentary. Don't get your reaction to it. Splunk Enterprising X Man's data access with data fabric search and data stream processor powers Uses with context and collaboration keywords context in their collaboration. House search is a hard problem. Discovery. We've seen carnage and people trying things. You guys do a lot of data. Lot of diverse date has been a big team here, right? Your customers have grown with more data coming in. Why these two features important. What's the keys? Behind the fabric search on the data processor is that the real time is the date acceleration. What are some of the key value points? What people know about the fabric surge processor. >>So actually, let me start with the data stream processor. You know, with DSP, what we're really doing is looking at streaming data. So when you think about the real time customers I ot sensor data, anything that's coming on the wire data stream processor lets you bring that in display. Now, the uniqueness of data stream processor is you wanted Thio, you didn't have to bring it in. Splunk. You can actually like process that live on the wire and it works just as well. Not do fabric search. It's, you know, you alluded to this earlier. It's how do you search across your massive data leaks warehouses that exist without having to bring it all in one place. So in the product, he notes Demo. Today we showed a really cool demo of a business and bliss user, really solving a business problem while searching across S three Duke and data that's sitting in instruct and then with the fabric search, you can also do massive, like federated, like global size searches on the context and collaboration. That's really once you have all this data in Splunk, how do you How do you like your users? Consume it right? And that's the mobile connected experiences A cz well, a cz Phantom and Victor Rapps like really activating this data in automating it. >>I want to get your thoughts on something that we've been seeing on the Q. And I've been kind of promoting for about a year now, and it really came back for you. Go back to the early days of duping big data. And, you know, you know, those days getting diverse data is hard. And so because it's a different formats on the database scheme is Andorran structured to find that databases in a way hamper hinder that capability. We've been saying that diverse data gives a better machine, makes machine learning better. Machine learning is a day I provides business benefits. This flywheel is really important. And can you give an example of where that's playing out and spunk? Because that seems to be the magic right now. Is that getting the data together, knowing what day it is? No blind spots. As much as that is, it's possible. But getting that flag will doing better. Better diverse data, better machine learning better. Ay, I better I better business value. I >>think it comes down to the word divers, right? So when you're looking at data coming in from many different sources, you also get a holistic perspective on what's going on in your business. You get the insight on what your customers may be doing in engaging with your business. You get insight on how your infrastructure is performing and the way you can optimize people to the business from you know you need to. The ops and operations is to like how customers are working and interacting with your business. The other piece is when you think about machine learning in the I A. CZ, you automate this. It's a lot easier when you have the holistic context, right? So, you know, diverse data means more context. More context means better insight into what you're trying to get to. It's just gonna rounds out. The perspective I often refer to it is it's adding a new dimension to something you already know >>and opens up a whole nother conscious around. What is the practitioners? Role? Not just a database administrator is setting up databases because you're getting at, you know, context is important. What's the data about the data? What dough I keep what should be addressable foran application. Is this relevant content for this some day, it is more valuable than others at any given time, so address ability becomes a big thing. What's your vision around this idea of data address ability for applications? >>So, you know, just going back to what you said about the administrators and the doers we call them the doers there. The innovators right there. The bill, people building the cool stuff. And so when you actually can bring these elements in for them, you really are giving them the ability to innovate and do better and have that accessibility into the information and really kind of like, you know, like Bill the best that they could write. So, you know, we've been saying Turn data into doing and it really is true. Like these are again the architects of what's happening and they're the people, like taking all this diverse data, taking the machine, learning, taking the technology of the building blocks and then turning it into, like, hold doing that we d'oh! >>It's interesting with markets change him. It actually changed the role of the database person makes them broader, more powerful. >>Yes, and because you know they're the ones fueling the business. >>Thanks for coming. I really appreciate the insight. I wish we had more time on a personal question. What's exciting You in the industry these days? Actually, you're exploring. Companies continue to grow from start up the i p o massive growth now to a whole nother level of market leadership to defend that you put some good products out there. What? What are you getting excited about these days from tech standpoint? >>You know, I think it's we're finally getting it. We're finally getting what you know. Being a data to everything. Platform is, for example, right after the keynote. I had more than a few people come up to me and say, Well, you know, that made sense, right? Like when we think about Splunk is the data to everything platform on what data platforms are meant to dio and how they should operate. So I think the industry is finally getting their What's exciting me next is if you look behind us and all the industry traction that we're seeing. So you know, taking technology and data beyond. And really enabling businesses from financial service is to healthcare to manufacturers to do more. You know, the businesses that traditionally, like, maybe have not been adopting technology as fast as software companies. And now we're seeing that, and that's super exciting. >>You know, I always get into these kind of philosophical debates with people. Either on the Cube are are off the Cube, where you know what is a platform success look like, you know, I always say, I want to get your reaction to this. I always say, if it's got applications or things being enabled value on a healthy ecosystem, so do you agree with that statement? And if so, what's the proof points for Splunk on those two things? What is defining that? What a successful platform looks like? >>You know that I do agree with you. And when I think about a successful platform, it's if I look around this room and just see how you know, like New York Presbyterian as using Splunk Thio like we heard from Dell today an intel. So when you see the spectrum of customers using Splunk across a variety of successes, it's that super exciting to me that tells me that you know what it is everything when you say date it. Everything >>all right? We got a fun job these days. >>D'oh to be here. So it's great. >>Great to see you. Thanks for coming back on the Cube. I'm looking forward to catching up. I'm John Kerry here on the Cube. Let's see what she's awesome. Cube alumni from 2014. Now it's blonde leading the product efforts and marketing. I'm John. Where were you watching the Q. Be right back after this short break