>> Narrator: Live, from Las Vegas, it's The Cube. Covering InterConnect 2017. Brought to you by IBM. >> Welcome back, everyone. Live here in Las Vegas, this is The Cube's coverage of IBM's Interconnect 2017. I'm John Furrier with my co-host Dave Vellante. Our next guest is Eric Herzog, Cube alumni, Vice President of Product Market at IBM storage. Welcome back to The Cube. Good to see you with the shirt on. You got the IBM tag there, look at that. >> I do. Well, you know, I've worn a Hawaiian shirt now, I think, ten Cubes in a row, so I got to keep the streak going. >> So, pretty sunny here in Vegas, great weather. Storage is looking up as well. Give us the update. Obviously, this is never going away, we talk about it all the time, but now cloud, more than ever, a lot of action happening with storage, and data is a big part of it. >> Yeah, the big thing with us has been around hybrid cloud. So our software portfolio, the spectrum family, Spectrum Virtualize, Spectrum Protect, our backup package, Spectrum Scale, our scale out NAS, IBM Cloud Object Storage, all will move data transparently from on-premises configurations out to multiple cloud vendors, including IBM Bluemix. But also other vendors, as well. That software's embedded on our array products, including our VersaStack. And just two weeks ago, at Cisco Live in Melbourne, Australia, we did a announcement with Cisco around our VersaStack for the hybrid cloud. >> So what's the hybrid cloud equation look like for you guys right now, because it is the hottest topic. It's almost like brute force, everywhere you see, it's hybrid cloud, that's what people want. How does it change the storage configurations? What's the solutions look like? What's different now than it was a year ago? >> I think the key thing you've got to be able to do is to make sure the data can move transparently from an on-premise location, or a private cloud, you could have started as a private cloud config and then decid it's OK to use a public cloud with the right security protocols. So, whether you've got a private cloud moving to a public cloud provider, like Bluemix, or an on-premises configuration moving to a public cloud provider, like Bluemix, the idea is they can move that data back and forth. Now, with our Cisco announcement, Cisco, with their cloud center, is also providing the capability and moving applications back and forth. We move the data layer back and forth with Spectrum Virtualize or IBM's copy data management product, Spectrum Copy Data Management, and with Cloud Center, or the ECS, Enterprise Cloud Sweep, from Cisco, you can move the application layer back and forth with that configuration on our VersaStacks. >> So this whole software-defined thing starts, it started when people realized, hey, we can run our data centers kind of the way the big hyper-scalers do. IBM pivoted hard toward software-defined. What's been the impact that you've seen with customers? Are they actually, I mean, there was a big branding announcement with Spectrum and everything a while back. What's been the business impact of that shift? >> Well, for us, it's been very strong. So if you look at the last couple quarters, according to the analysts that track the numbers, from a total storage perspective, we've moved into the number two position, and have been, now for the last two years. And for software-defined storage, we're the number one provider of software-defined storage in the world, and have been for the last three years in a row. So we've been continuing to grow that business on the software-defined side. We've got scale-up block configurations, scale-out block configurations, object storage with IBM Cloud Object Storage, and scale-out NAS and file with our IBM Spectrum Scale. So if you're file, block, or object, we've got you covered. And you can use either A, our competitor's storage, we work with all our competitor's gear, or you could go with your reseller, and have them, or your distributor provide the raw infrastructure, the servers, the storage, flash or hard drives, and then use our software on top to create essentially your own arrays. >> So when you say competitor's gear, you're talking about what used to be known as the SAN Volume Controller, and now is Spectrum Virtualize, right? Did I get that right? >> Yes, well, we still sell the SAN Volume Controller. When you buy the Spectrum Virtualize, it comes as just a piece of software. When you buy the SAN Volume Controller as well as our FlashSystem V9000, and our Storwize V7 and V5000, they come with Spectrum Virtualize pre-loaded on the array. So we have three ways where the array is pre-loaded: SAN Volume Controller, FlashSystems V9000, and then the Storwiz products, so it's pre-loaded. Or, you can buy the stand-alone software Spectrum Virtualize and put it on any hardware you want, either way. >> So, I know we're at an IBM conference, and IBM hates, they don't talk about the competition directly, but I have to ask the competitive questions. You've had a lot of changes in the business. Obviously, cloud's coming in in a big way. The Dell EMC merger has dislocated things, and you still see a zillion starups in storage, which is amazing to me, alright? Everybody says, oh, storage is dead, but then all this VC money still funneling in and all this innovation. What's happening in the storage landscape from your perspective? >> Well, I think there's a couple things. So, first of all, software-defined has got its legs, now. When you look at it from a market perspective, last quarter ended up at almost 400 million, which put it on a, let's say, a 1.6 to 2 billion dollar trajectory for calendar 2017, out of a total software market of around 16 billion. So it's gone from nothing to roughly 2 billion out of 16 billion for all storage software of all various types, so that's hot. All flash arrays are still hot. You're looking at, right now, last year, all flash arrays end up at roughly 25% of all arrays shipped. They're now in price parity, so an all-flash array is not more expensive. So you see a lot of innovation around that. You're still seeing innovation around backup, right? You've got guys trying to challenge us with our SpectrumProtect with some of these other vendors trying to challenge us, even though backup is the most mature of the storage software spaces, there's people trying to challenge that. So, I'd say storage is still a white-hot space. As you know, the overall market is flat, so it is totally a drag out, knock-down fight. You know, the MMA and the UFC guys got nothing on what goes on in the storage business. So, make sure you wear your flak jacket if you're a storage guy. >> Meaning, you got to gain share to grow, right? >> Yes, and it's all about fighting it out. This Hawaiian shirt looks Hawaiian, but just so you know, this is Kevlar. Just in case there's another storage company here at the show. >> So what are the top conversations now with storage buyers? Because we saw Candy's announcement about the object store, Flex, for the cold storage. It changes the price points. It's always going to be a price sensitive market, but they're still buying storage. What are those conversations that you're having? You mentioned moving data around, do they want to move the data around? Do they want to keep it at the edge? Is it moving the application around? What are some of those key conversations that you're involved in? >> So we've done a couple innovative things. One of the things we've done is worked with our sales team to create what we call, the conversations. You know, I've been doing this storage gig now for 31 years. Seven start-ups, IBM twice, EMC, Maxtor and Seagate- >> John: You're a hardened veteran. >> I'm a storage veteran, that's why this is a Kevlar Hawaiian shirt. But no CIO's a storage guy, I've never met one, in 31 years, ever, ever, ever met a storage guy. So what we have to do is elevate the conversation when you're talking to the customer, about why it's important for their cloud, why it's important for machine learning, for cognitive, for artificial intelligence. You know, this about it, I'm a Star Trek guy. I like Star Wars, too, but in Star Trek, Bones, of course, wands the body. So guess what that is? That's the edge device going through the cloud to a big, giant server farm. If that storage is not super resilient, the guy on the table might not make it. And if the storage isn't super fast, the guys on the table might not make it. And while Watson isn't there, yet, Watson Health, they're getting there. So, in ten years from now, I expect when I go to the doctor, he's just like in Star Trek, waving the wand, and boy, you better make sure the storage that that wand is talking to better be highly resilient and high performing. >> Define resilient, in your terms. >> So, resilient means you really can't have more than 30 seconds, 50 seconds a year of down time. Because whoever's on the table when that thing goes down has got a real problem. So you've got to be up all the time, and if you take it out of the healthcare space and look at other applications, whether you look at trading applications, data is the new gold. Data is the new diamonds. It's about data. Yes, I'd love to have a mound of gold, but you know what, if you have the right amount of data, it worth way more than a mound of gold is. >> You're right about the CIO and storage. They don't want to worry about storage. They don't want to spend a lot of time thinking about it. A CIO once said to me, "I care about storage like this, "I want it to be dirt cheap, lightning fast, and rock solid." Now, the industry has done a decent job with rock solid, I would say, but up until Flash, not really that great with lightning fast, and really not that great with dirt cheap. Price has come down for the hardware, but the management has been so expensive. So, is the industry attacking that problem? And what's IBM doing? >> Yeah, so the big thing is all about automation. So when I talk about moving to the hybrid cloud, I'm talking about transparent migration, transparent movement. That's an automation play. So you want to automate as much as you can, and we've got some things that we're not willing to disclose yet that'll make our storage even more automated whether it be from a predictive analytics perspective, self-healing storage that actually will heal itself, you know, go out and grab a code load and put the new code on because it knows there's a bug in the old code, and do that transparently so the user doesn't have to do anything. It's all about automating data movement and data activity. So we've already been doing that with the Spectrum family, and that Spectrum family ships on our storage systems and on our VersaStack, but automation is the critical key in storage. >> So I wonder, does that bring up new KPIs? Like, I presume you guys dog food your own storage internally, and your own IT. >> Eric: Yes >> Are you seeing, because it used to be, OK, the light's green on the disc drive, and you know, this is our uptime or downtime, planned downtime, you know, sort of standard metrics that we've known for 30-40 years. With automation, are we seeing a new set of metrics in KPIs emerge? You know, self-healing, percentage of problems that corrected themselves, or- >> Well, and you're also seeing things like time spent. So if you go back to the downturn of seven, eight, and nine, IT was devastated, right? And, as you know, you've seen a lot of surveys that IT spend is basically back up to '08, OK, the pre-08 crash. When you open up that envelope, they're not hiring storage guys anymore, and usually not infrastructure guys. They're hiring guys to do devops and testdev, and do cloud-based applications, which means there's not a lot of guys to run the storage. So one of the metrics we're seeing is, how much guys do I have managing my storage, or, my infrastructure? I used to have 50, now I'm a big bank, can I do it with 25? Can I do it with 20? Can I do it with 15? And then, how much time do they spend between the networking, the storage, the facilities themselves. These data center guys have to manage all of that. So there are new metrics about, what is the workload that my actual human beings are doing? How much of that is storage versus something else? And there's way less guys doing storage as a full-time job, anyway, because what happened in the downturn? And, so automation is critical to a guy running a datacenter, whether he's a cloud guy, whether he's a small shop. And clearly in the Fortune, global 2500, those guys, where they've got in-house IT, they've cut back on the infrastructure team and the storage team, so it's all about automation. So, part of the KPIs are not just about the storage itself, such as uptime, cost per Gig, cost per transaction, the bandwidth, you know, those sorts of KPIs. But it's also about how much time do I really spend managing the storage? So if I've only got five guys, now, and I used to have 15 guys, those five guys are managing, usually, three, to four, to five times more storage than they did in 2008 and 2009. So now you've got to do it with five guys instead of 15, so there's a KPI, right there. >> So, what about cloud? We heard David Kinney talk today about the object store with that funny name, and then he talked about this cloud-tiering thing, and I couldn't stay. I had to get ready for theCube. How do you work with those guys? How do you sell a hybrid story, together, because cloud is eating away at the traditional infrastructure business, but it's all sort of one big, happy family, I'm sure. But how do you work with a cloud group to really drive, to make the water level higher for IBM? >> So, all of our products from the Spectrum family, not all, but almost all our products from the Spectrum family, will automatically move data to the cloud, including IBM Bluemix/SoftLayer. So our on-premises can do it. If you buy our software only, and don't buy our storage arrays, or don't buy a Storwize, or don't buy a flash system, you still can automatically move that data to the cloud, including the IBM cloud object store. Our Spectrum Scale product, for example, ScaleOut NAS, and file system, which is very highly used in big data analytics and cognitive workloads, automatically, by policy, will tier-data to IBM cloud object storage. Spectrum Protect can be set up to automatically take data and back it up from on-premises to IBM cloud object storage. So we've automated those processes between our software and our array family, and IBM cloud object storage, and Bluemix and SoftLayer. And, by the way, in all honesty, we also work with other cloud vendors, just like they work with other storage vendors. All storage vendors can put data in Bluemix. Well, guess what, we can put data in clouds that are not Bluemix, as well. Of course, we prefer Bluemix. We all have IBM employee stock purchase, so of course we want Bluemix first, but if the customer, for whatever reason, doesn't see the light and doesn't go to Bluemix and goes with something else, then we want to make sure that customer's happy. We want to get at least some of the PO, and our Spectrum family, and our VersaStack family, and all of our array family can get that part of the PO. >> You need versatility to be on any cloud. >> Eric: We can be on any cloud. >> So my question for you is, the thing that came out of our big data, Silicon Valley event last week was, Hadoop was a great example, and that's kind of been, now, a small feature of the overall data ecosystem, is that batch and real time are coming together. So that conversation you're having, that you mentioned earlier, is about more real time than there is anything else more than ever. >> Well, and real time gets back to my examples of Bones on Star Trek wanding you over healthcare. That is real time, he's got a phaser burn, a broken leg, a this and that, and then we know how to fix the guy. But if you don't get that from the wand, then that's not real time analytics. >> Speaking of Star Trek, just how much data do you think the Enterprise was throwing off, just from an IOT standpoint? >> I'm sure that they had about a hundred petabytes. All stored on IBM Flash Systems arrays, by the way. >> Eric, thanks for coming on. Real quick, in the next 30 seconds, just give the folks a quick update on why IBM storage is compelling now more than ever. >> I think the key thing is, most people don't realize, IBM is the number two storage company in the world, and it has been for the last several years. But I think the big thing is our embracing of the hybrid cloud, our capability of automating all these processes. When they've got less guys doing storage and infrastructure in their shop, they need something that's automated, that works with the cloud. And that's what IBM storage does. >> All right, Eric Herzog, here, inside theCube, Vice President of Product Market for IBM Storage. I'm John Furrier, and Dave Velante. More live coverage from IBM InterConnect after this short break. Stay with us. (tech music)

from Las Vegas accepting the signal from the noise it's the kue coverage interconnect 2016 brought to you by IBM now your host John hurry and Dave vellante okay welcome back around we are here live in Las Vegas for IBM interconnect 2016 special presentation of the cube our flagship program would go out to the events and extract the signal from the noise I'm John forreal echoes gave a lot they are next guest pricing Kohler who's the chief information technology officer and I'm saying this for the first time on the cube the weather company and IBM business welcome back to the cube thank you very much glad to be back last time you weren't an IBM business we were just the weather company were just the weather company so congratulations on your success want to say we really big fans of it but what Papa Chiana the team have done is visionary bold and very relevant so congratulations hey how's it feel it is grateful din we are really excited the opportunity with the IBM platform and you know the reach and the capabilities I mean it it really helps accelerate what we were trying to get done as the weather company you know as our own standalone business um and you know as you try to prepare and protect the entire planet all of its people and all of its businesses prepare and protect them for tomorrow which is really what the weather is company is all about finding that intersection of consumer behavior helping prepare and protect you as a in your personal life and your family but also you as a business owner how do we prepare and protect you to do better tomorrow because of the weather and the insights that we can provide fit straight into the work the Bob picciano in team have been doing with the insights you know economy with Watson and analytics with insights as a service all of that just kind of plugs together in it it really is a natural fit it's interesting to see IBM's move we were asked to guess on from IBM earlier and Jamie Thomas said it's all open source we want to get in early so this is an early bet for IBM certainly a bold move with the weather company but it's interesting the scuttlebutt as we talk to our sources inside the company close to the company have telling us that the weather companies is infiltrating and affecting the DNA IBM in a good way and you guys have always been a large scale data company and that is what all businesses are striving to digitize everything yes and so take us through that I mean one I think it's fair to say that you guys are kind of infecting I play in a positive way the mindset of being large-scale data yeah well why is that so compelling and how did you guys get here obviously whether the big data problem share some commentary around where it all came from well i think you know it's in my DNA first of all and it's in our company's DNA it's are no teams DNA you know I'm a change agent you would not want to hire me to maintain something good if you want to hire me to you know to break something and rebuild it better that's I'm your guy so you know I think when you look at the movement from you know the kind of the movement over time of IBM and you know the constant evolution that IBM goes through time is ripe when you take the cloud capabilities and you take data and you take analytics and the whole concept and capabilities of Watson Watson gets smarter as it learns more Watson can only be as smart as the data you feed it and so for Watson to continue to learn and continue to solve new problems and continue to expand its capability set we do have to feed it more data and and so you know looking at whether whether it was the original big data problem ever since the first mainframe the first you know application ever written on a mainframe was a weather forecast and ever since then everybody's been trying to figure out how to make the forecast more accurate and a lot of that comes from more data the more data you have the more accurate your forecast is going to be so we've been trying to solve this big data problem Walt and Dave talks about it was saw earlier in the opening about digital assets and in this digital transformation companies have to create more digital assets that's just dating yeah in this new model so when you look at the data aspect you say whether also is a use case where people are familiar with we were talking before we went on camera that people can understand the geekiness of whether it's different they're familiar with it but also highlights a real-life use case and the IOT Internet of Things wearables we heard you have sports guys on here tracking sensors this brings up that digital digitizing is going to be everything not just IT right it makes it real right if I think about my parents right we've been talking about IOT hey dad you're gonna have a connected refrigerator why does he care what do I need a connected refrigerator for but as you start to bring these insights to life and you make them real and you say you know what if I actually understand the humidity levels in your house and I can get that off the sensor on the air intake of your refrigerator I can now correlate that the humidity level outside of your house and I might be able to actually tweak your HVAC and I can make that run efficiently and I can now you know cut thirty percent of your cooling costs and all of these you know examples they're integrated they become real yeah and and I think weather is great because everybody checks their weather app the weather channel app or the weather underground app every day they're always looking at it and you know we get it right seventy-eight percent of the time we'd get it wrong sometimes we're constantly working to maintain our number-one position and data accuracy on weather forecasting and you know the more data we have the more accurate we can make it and so we've got any safer to you think just think about the use cases of people's lives slippery rose you know events correct I mean it's all tied in no goes back to another you know if I understand what's going on with the anti-lock braking system of a car and I already have a communication vehicle into everybody in that car which is our appt in their pocket I can alert them if the car is up ahead are having here are their abs activated and if all of the cars up ahead are having their abs activated I could alert them two miles back and say hey get ready slow down it's real it's not forecasted it's real data I'm giving you a real alert you should really take action and you know as we move from you know weather-alerts that we're looking out forward in time many hours as we're now doing rain alerts where we tell you it's going to start raining in the next seven minutes ten minutes people love those because it's right now and I can make a decision right now lightning strikes are always fascinating oh god because I gotta see crisis so last fall at IBM insight we interviewed David Kinney death your CEO and then right after I think was the week after I was watching some you know I was in Boston watching some sports program and there's bill belichick complaining about the in accuracy of whether i'll try that whether some reporter asked him about you know you factor in the weather i don't even pay attention i look at the weather forecast they're always wrong as a wait a minute I just I just interviewed David Kennedy he was bragging on the weather is the accuracy and how much it's improved so helping you mentioned seventy-eight percent of the time it's it's gotten better over time it has it still got rooms we're not perfect so so talk about that progression it is the data but how much better are you over time where is that better is it just short term or is it longer term at so color to that it's a great question and it's a fair point I think one of the biggest changes we've made in the last three years that the weather company is we've taken our forecast from what was roughly 2 million locations where we would do a forecast two million locations around the globe and today we we create a forecast for 2.2 billion locations around the globe because the weather is different at Fenway then Boston Logan it's just different than the the start time of rain the start time of a thunderstorm you know that's gonna be different now maybe five minutes but it's different the temperature the wind it's different and so as we've increased the accuracy and granularity of ours are our locations we've also done that from a time perspective as well so we used to produce a forecast every four to six hours depending upon how fast the models ran and did they run and complete successfully we now update our forecast every 15 minutes and so we we've increased the the you know all aspects of that and when you when you now think about getting your weather forecast you can no longer just type in BOS for your airport code and say i want to know what the weather is at boston logan if you're you know if you're in cambridge the boston logan forecast is not accurate for you you know five years ago every that was fine for everybody right right and so we have to retrain people to think about and make sure that when they're looking for a forecast and they're using our apps they can get a very specific forecast for where they are whatever point on the globe they are and and don't have you know Boston you know Logan as your you know favorite for your city if you're sitting in Cambridge or your you know you know it in Andover further outside where I am now where you gonna be my guess I gotta get so different you leverage the gps capabilities get that pinpoint location it will improve what the forecast is telling so I feel like this is one of those omni headed acquisition monsters for lack of a better term because when the acquisition was first announced is huh wow really interesting remember my line Dell's by an emc IBM is buying the weather company oh how intriguing it's a contrast it's all about the data the Dane is a service and then somebody whispered in my ear well you know there's like 800 Rockstar data scientists that come along with that act like wow it's all about the data scientists and then on IBM's earnings call i hear the weather company will provide the basis for our IOT platform like okay there's another one so we're take uh uh well i think IBM made a very smart move i'm slightly biased on that opinion but I think I be made a very smart move at very forward-looking move and one built on a cloud foundation not kind of a legacy foundation and when you think about IOT data sets we ingest 100 terabytes of data a day i ingest 62 different types of data at the weather company i ingest this data and then i distributed it massive volumes so what we had fundamentally built was the world's you know largest cloud-based iot data platform and you know IBM has many capabilities of their own and as we bring these things together and create a true next-gen cloud-based IOT data engine the ability for IBM to become smarter for Watson to become smarter than all of IBM's customers and clients to to become smarter with better applications better alerts better triggers and that alerts if you think about alerting my capability to alert hundreds of millions of people weather-alerts whether that's a lightning alert a rain alert a tornado warning whatever it is that's not really any different than me being able to alert a store clerk a night stock clerk at the local you know warehouse club that they need a stock you know aisle three differently put a different in cap on because we now have a new insight we have a new insight for what demand is going to be tomorrow and how do we shift what's going on that alert going down to a handheld device on the guy driving the four club yeah it's no different skoda tato yeah the capability to ingest transform store do analytics lon provide alerting on and then distribute data at massive scale that's what we do we talk about is what happened when Home Depot gets a big truck comes in a bunch of fans and say we know where this know the weather company did for you yeah we don't understand you'll understand you'll fake it later they file a big on the top of it so I OT as well as markets where people don't can't understand that some people don't know it means being like what's IOT Internet of Things I don't get it explain to them some little use cases that you guys are involved in today and some of these new areas that you're highlighting with with learning somehow see real life examples for for businesses and users there is a smarter planet kind of you know safe society kind of angle to it but it's also there's a nuts-and-bolts kind of practical if business value saving money saving lives changing you know maintenance what are some of the things share the IOT so there's there's only two things there so one is what is IOT and IOT really is is sensor data at the end of the day computers sensors electronic equipment has a sensor in it usually that sensor is there to do its job it's there to make a decision for what if it's a thermostat it has a sensor in it what's the temperature you know and so there are sensors in everything today things have become digitized and so those sensors are there as next as those next evolutions have come online those those sensors got connected to the Internet why because it was easier than to manage and monitor you know you know here we are at the mandalay bay how many thermostat sensors do you think this hotel casino complex has thousands and so you can't walk around and look at each one to understand well how's the temperature doing they all needed to be shipped back to a central room so that the in a building manager could actually do his job more efficiently those things then got connected so you could look at it on a smartphone those things they continued to get connected to make those jobs easier that first version of all of those things it was siloed that data SAT within just this hotel but now as we move forward we have the ability to take that data and merge it with other data sets there's actually a personal a Weather Underground personal weather station on the roof of the Mandalay Bay and it's actually collecting weather data every three seconds sending it back to us we have a very accurate understanding of the state of the Earth's atmosphere right atop this building having those throws is very good for the weather data but now how does the weather data impact a business that cares about the weather that has there we understand what the Sun load is on the top of this building and so we can go ahead and pre-heat your pre cool rooms get ahead of what's changing out sign that will have an impact here inside we have sensors on aircraft today that are collecting telemetry from aircraft turbulence data that helps us understand exactly what's going on with that airplane and as that's fed in real-time back down to the earth we process that and then send it back to the plane behind it and let that plane behind it know that it needs to alter it course change its flight plan automatically and update the pilots that they need to change course to a smoother altitude so gone are the days of the pilot having to radio down and fall around his body it's bumpy to get these through there anywhere machines can can can do this in real time collected and synthesize it from hundreds of aircraft that have been flying in that same route now we can actually take that and produce a better you know in flight plan for those for those machines we do that with with advertising so you know when you think about advertising you be easy the easy example is hey we know that you're going to sell more of X product when y weather condition happens that's easy but what if I also help you know when not to run an ad how do I help save you money you know if I know that there's no way for me to actually impact demand of your product up or down because we know over the course of time looking at your skew data and weather data that no matter what what we do weathers gonna have this impact on your product save your money don't run an ad tomorrow because it doesn't matter what you do you're not going to actually move your product more that's great and it's much business intelligence it's all the above its contextual data help people get insights in subjective and prescriptive analytics all rolled into one in a tool that alerts the actual person may explain to people out they were predictive versus prescriptive means a lot people get those confused what's your how would you prescriptive is you know where we want data that just tell us what to do based upon historic looking trends so i can take ten years of weather data and I can marry that up with ten years of some other data set and I can come up with you know a trend based upon the past and with that then I could prescribe what you should do in the future hey looks like general trend bring an umbrella tomorrow it's good it might rain but if I get into predictive analytics now I can start to understand by looking at forward-looking data things that haven't happened yet or new data sets that I'm merging in in real time oh wait a minute we thought that every time it rained more people went to this gas station to fill up but wait a minute today there's an accident on the road and people no matter what we do they're not going to go to that gas station because they're not even going to drive by it so being able to predict based upon feet of our real-time data but also forward-looking data the predictive analytics is really around the insights that we want to guess I got to ask you one question about the IBM situation and I want you to kind of reflect get him get you know all right philosophical for a second what's the learning that you've had over the past few weeks months post-acquisition inside IBM is there a learning that you to kind of hit you that you didn't expect there's something you'd expect what sure what was your big takeaway from this experience personally and you had some great success in the business now integrated into IBM what's the learning that cuz that's comes out of this for you I am really proud of the team at the weather company you know I I think what we have been able to accomplish as a small company you know comparative to my four hundred and sixty-eight thousand colleagues at IBM yeah what we've been able to accomplish what we've been able to do is really you know it's impressive and I've been proud of my team I'm proud of our company I'm proud of what we were able to get done as a company and you know the reflection really is as you bring that into IBM how do you make sure that you can you can now scale that to benefit such a large organization and and so while we were great at doing it for ourselves and we built an amazing business with amazing growth you know attracted lots of people that looked at buying us and obviously IBM executing on that I think that's amazing and I'm proud of that but I think my biggest reflection is that doesn't necessarily equate to success at IBM and we now have to retool and retrans form ourselves again to be able to take what we know how to do really well which is build great capabilities build big data platforms build analytics engines and inside engines and then armed a sea of developers to use our API we can't just take what we've done and go mate rest on your laurels you gotta go reinvent so I think my biggest you know real learning and take away from the kind of integration process is well we have a lot to learn and we have a lot of change we need to do so that we can actually now adapt and and continue to be us but do it in a way that works as an IBM ER and and that's that's there's there's going to be an art to this and we've got a ways to learn so I'm going in while eyes wide open around what I have to learn but I also am very reflective on on how proud I am as a leader of the team that you know has created you know such an amazing capability acquisition is done you savor it you come in you get blue washed and I hope I had a Saturday afternoon where I say okay got all like what is this gonna think so and then okay so you you wake up in the morning and you sort of described at a high level you know what you're doing but top three things that you're focused on the next you know 12 12 months so so you know the biggest thing that I'm focused on number one is making sure that we protect the weather company culture and how we know how to do and build great things and so I've got to lead us through obviously becoming integrated with IBM but not losing who we are and IBM is very supportive of that you know Bob picciano his team have been awesome and you know John Kelly and team have been awesome everybody that we have worked with has been so supportive of Bryson please make sure you find the right way through this we don't want to break you and I think that's natural for any acquisition for any yeah but you guys aren't dogmatic you were very candid saying we're gonna transform ourselves and adapt absolutely and so and so so we've got that on wrestling on my mind how do we go find immediate wins there's there's a a million different ways for us to win there's thousands of IBM sales teams that are out in front of clients it's just today with new problems how do we quickly adapt what we've been good at doing and help solve new problems very quickly so that's on my mind and then you know wrapping that in a way that becomes self service we can't I don't want to scale my team through people to solve all these problems I want to find a way to make sure that all these capabilities new data sets new insights new capabilities that we bring the life I want to do that in a self-service way I want to make sure that our technology the way we interact with developers the developer community that we bring in to kind of work on our behalf to make this happen I don't want to solve all these problems I want to enable others to solve the problems and so we're very focused on the self service aspect which i think is very new prices thank you so much taking the time out of your busy schedule to see with us in the queue good to see you again or any congratulations IOT everything's a sensor that we're a sense are here in the cube and we sense that it's time to go to SiliconANGLE DV and check out all the videos we have a purpose our sensor is to get the data to share that out with you thanks for the commentary and insight appreciate it whether company great success weather effects of song could affect stock prices all kinds of things in the real world so we had a lot of a lot of big data thank you very much look you here live in Las Vegas right back more coverage at this short break