>> Announcer: From San Francisco, it's The Cube. Covering, OSIsoft, PI World 2018. Brought to you by OSIsoft. >> Hey, welcome back everybody, Jeff Frick here with the Cube. We're at OSIsoft in downtown San Francisco for PI World 2018. About 3,000 people talking about really, OT, operations as it slowly marries with IT. Industrial Internet of Things, they've been doing it here for a long time and we're excited to have our next guest and practitioners out in the field who got solutions and they are actually doing good work, so, Sanket Amberkar, he's the SVP of Falkonry, sorry about that, welcome. >> No problem. >> And Michael Risse the VP at Seeq, welcome. >> Yes. Thank you very much. >> So, before we get started just a quick summary of what your companies do. >> Sure, so in the case of Falkonry we do what is called operation machine learning, and what it means is really applying machine learning to business operations and data analytics to really drive improvement and efficiencies in their operations. And what's unique about that is it's kind of like a data scientist in a box, so you don't require a data scientist on your side, you can actually have your own practitioners and operations people use it. >> And just plug into your algorithms? >> And just plug it into what exists in their infrastructure. >> Okay, and what about Seeq? >> So, Seeq is an analytics application for process manufacturing data, for example OSIsoft PI, and really what our focus is, there's incredible innovation out there, the open source and the machine learning and the big data and so forth, and we're about closing the gab between what's possible and what's practical, in terms of the applications that people use everyday in process manufacturing. >> So, it's just funny cause big data is all the rage and machine learning is all the rage and AI and the Industrial Internet of Things and IoT, and yet these guys have been doing it for like 40 years. (laughs) Without IP based sensors, without 5G, without Hadoop 40 years ago. So, why have we not heard about this and what kind of opportunities now open up when the rest of kind of the IT infrastructure space and we do get 5G and we do have IP connected devices and everybody's ready to get this censored data it's a whole new revolution. >> Exactly, because what we're seeing right now is people have data in their systems, they just haven't leveraged it to the full capability. So, as you start getting more and more data and especially if you have a PI system, you have access to all that data now. How can you fully leverage what you have and really drive new insights from that, and that's really what's driving all this stuff and you know you brought up some good points with wifi and 5G and other sources where information which was initially not connected can now be connected. You have now full visibility into your entire systems, and you can actually be able to control things that before you had to send a person out there and kind of go and tweak and turn and get working. So, it's really changing how you digitize your infrastructure, its become a bit of a buzzword unfortunately, but digitization of your industrial operations is actually real and it's happening right now. >> Right. >> It's funny you bringing that up, because you could argue that original big data was manufacturing data, they were just missing a branding team to call it something cool, right? (laughs) So, the original big data was manufacturing data, there's a lot of it, there's been a lot for a long time. Now, they are ahead in the sense that they know how to store it and do a great job at the PI infrastructure, for example, and now as you said, it's about that next step. Not only for the manufacturing environment but for those IoT environments that are just starting to collect and process data. So, now if we can close the gap on modern analytics, right and with the modern analytics capabilities with the data they've collected, what that means is businesses are going to get more benefits. It's not about sensors, it's not about data collection, it's about business benefits to the bottom line. >> Jeff: Right, right. >> The ability to see then get insights from data. >> So, it's really interesting you know because so many start-ups get started because they see some inefficiency. Whether it's empty rooms that can be Air B&B or it's cars that sit 90 percent of the time that can turn into an Uber or a Lyft. You would think that in some of these old line manufacturing that a lot of that inefficiency would have already been rung out but as we keep hearing stories here time and time again, whether it's getting better yield out of your gold ore, or getting better yield out of your water systems, there's still a ton of inefficiencies and opportunity yet to be extracted and that's before we add machinery. >> Well, that's the difference between I've got the data and I've got the science or I've got the calculations. It's too hard and takes too long to get the insight to impact the outcome, if that makes sense. It takes me more time to do the analysis in a spread sheet, right, or a pen or paper, >> Jeff: Right. >> Then to impact the outcome the batch, I'm not going to do it, but with these modern analytics, I can get the insight quickly and I can make a change to what I'm doing or prevent something from happening and now it's worth doing. So, I've got the data, got the insights. >> And if you think about like today, for example, you have controls systems in place that have been there for 20 years, that basically do what we call, Real-Time Control, so, you're doing a batch process and you're monitoring that stuff, it can do that stuff perfectly well. Does it make sense to put something new just to make another two percent, maybe not, but what about if you can now predict not just real time but predict what's going to happen six hours, 12 hours, two days, a week ahead of time, that's entirely brand new. And the problem is looking at your data you have today, there's just way too much data for you to humanly possibly do that. So, therefore it never really got touched as much. Now is you have the tool sets that have come from the IT side, have come from (unintelligible), now you apply them over here. Suddenly, you're uncovering basically net new benefits that you can get, that just before were not easily accessible. >> Jeff: Right, right. >> I was just going to say 30 years after all the data was created and collected, unplanned downtime, right, is still a bugaboo of so many of these industries. Unplanned downtime means whoops, we didn't expect that to happen. Machine failure, something going down, another set of analytics is going to be required to really stamp that out >> Jeff: Right. >> And know things in advance as Seeq just pointed out. >> So, what are the notions that gets kicked around a lot right as data's the new oil rut, And I'm not going to go there but one thing that is clear is that data used to be a liability, it used to be expensive to store, expensive to keep and you hear time, I mean there's a really great movie, was sponsored by EMC, big data movie that they did and they talked, it was a horrible story about these EKG machines that would be kicking out data all the time on a tape that would go to the floor with predictive data that could tell you when someone's having an issue but the nurses only came in and checked at once an hour or whatever the protocol was. It's just horrible. So, have the industrial companies now realized that beyond what's on their balance sheet and their capital expense and these huge infrastructure projects, they actually have a lot of value in their data. We see it in tech companies all the time. Why do these companies have this valuation? It's not a multiple revenue, it's because they got the data. But we haven't really seen it morph into more old line asset-based companies where there isn't a line in them yet. Soon, it's going to be interesting to see how the accounting principles change where you get credit for this data. People getting it now, are they seeing the value? >> Absolutely, they're getting it. The pressure that they have to now realize the benefits of the data possibility, mean that they recognize that look, my next benefit out of my balance statement comes from my, Mackenzie calls it competing on analytics, my ability to do analytics drives that balance sheet results. Okay, now what are the right analytics and what am I looking for in terms of outcomes? So, they absolutely get it. It's just been too hard, the gap between the innovation and our consumer and IT lives and what's been generally available and the OT space has been too high for too long. >> Jeff: Right. >> And that's what we're working on closing. >> And there's two things actually, you bring up a good point with the Mackenzie article because Mackenzie's predicting that 20 percent, actually, the next 20 percent increase in productivity rises actually come from data analytics being applied to manufacturing and being flied to process operations. >> Jeff: Right, right. >> And it's interesting because it's not like this stuff did not exist before, if you look at it right now, there's about 15 percent adoption rate of advanced analytics in manufacturing, and I'm not talking about your standard real time stuff, I'm talking more the advanced. But, if you look at the adoption, what's expected by 2020 they're saying that's going to go up to 53 percent, of all manufacturing out there, all process of each other. So, what it means is right now, this year 2018 and 2019 is we're going to see a huge amount of adoption where people have been doing pilots until now maybe or doing a little big of trials up to now, actually, they have stepped in and we're seeing real purchase orders for real production applications and it's happening in every industry, that's interesting thing too, it's not just, before it used to be semiconductors are leading or automotive is leading or maybe oil and gas. We're seeing it in pretty much every single one right now because everyone has the data, everyone knows it's not being utilized and they're saying, "Where can I get my next advantage from?" because it is a competitive advantage now. If your competitor is doing a better job at their data than you are, then you want to make sure that you are able to leverage it yourself. >> Goldman Sachs actually wrote an article on productivity on (unintelligible) and shell from brawn to bites to brains and the whole point was the next chunk of innovations is going to come from the brains and the analytics that are possible and how to optimize those outcomes. >> Jeff: Right. >> So, it's very clearly seen. >> So, the other buzz that's happening writers of the all the machines are going to take our jobs and the universal basic income will lay on the beach or being laying out and you're on market street one of the three, I'm not sure which. But, clearly the evidence is contrary and really we're seeing that here especially with some of the stuff even without the analytics, it's a combination of the machine with the data and a little bit of an application on top of that to an able people to make their decisions and some of used cases that have been coming out of this show are fascinating to me. The scale of impact, one of the water companies that are losing like 50 percent of the water between the time it goes out of the processing plant to the spicket at the house. 50 percent! >> Michael: Right. >> These are humongous. Huge inefficiencies. So, the opportunity just seems endless. I was just going to say, do you have any of your favorite stories where it's just mind blowingly, in hindsight maybe obvious but it wasn't at the time until they actually dug into this data a little bit. >> Sure. So, you bring up a really good point because it's not really about replacing any work, it's actually augmenting what the work can do. You're making them much more efficient with what they're able to do because they're the ones making the decisions at the end of the day. There's a couple of interesting news cases that we've been seeing and I'll give you one coming from the mining side, where for example, they've been having an issue where on the conveyor belt depending on the quality of the ore that ore was starting to get blocking into the part of the machine that does the crushing and does the grinding and that when it goes down is about 30 thousand dollars per hour, takes them somewhere between five hours to a full day, so that can be like 720 thousand dollars per day and it happens twice a week so you can do the math, >> Jeff: That's loss of productivity. >> That's loss of productivity right off the bat. >> And it happens twice a week. >> And this is not a massively large company, this is like a mining company on Wyoming having an issue like this. So, obviously there's a big problem over there to solve, and the beauty of it is, you can take the data, the data can absolutely anticipate and say three steps before it reaches that grinding part of the cycle that dispatch of ore which is moving through right now has a problem and therefore what they're able to do is they're able to go and slow the process down so you're still having output and productivity, have the ore removed, and then basically continue the process on. They got to the point where they're so confrent now that the actual operater now is able to close that loop remotely and basically whenever the warning happens, they can say yes, here's the bad batch, automatically get it taken off and it keeps going on. But you have the operate in the loop. The operate is the one making the decision, what to do about this. This is not being done for them. And while it helps in automating, it's not an automation, it's still a person in the loop. And that's always going to be the case. >> I just think one of the things that Falkonry and Seeq have in common is that focus on the engineer or the operator, the person and then taking advantage of their expertise, their experience, their education, they know a lot about those plans and assets. It's just too hard to do the analytics by hand. So, if they can use the Falkonry or Seeq to get the insight more quickly, then they get the better production result. But tapping rather than replacing that expertise and that engineering or that frontline worker absolutely critical because there's 20 or 30 years of experience in some of these plants and some of these assets. You want to tap what they know cause they've seen it. Just help them do something more quickly. >> That institutional law just really hard throughout the cake, and I still keep hearing about everything on Excel too. It's just fascinating, the market penetration of Microsoft Excel. >> 30 years later. >> I have my data on a CSV file, can you do something with it? >> Yes, can you do something with it. >> And it's from three weeks ago and I finally threw it out the export. So, before I let you guys go, thoughts on the show, we're here at OSIsoft. Have you been here before, >> Yep. >> It's our first time, I see people walking around with 15 year badges which is amazing, it's like the most successful company you've never heard about that's right across the bay and operating for 40 years. So, general impressions, some takeaways from some of the sessions, what are you guys here for? >> So, OSIsoft does a really great value for essentially the Industrial Operations Team because basically, they're bringing them data that actually can really change what they do in their operations, can really make a big difference and in terms of the users, they're really sophisticated, you don't have to convince them and say hey data is important, they know that data is important, they have been doing stuff with their data and they're able to actually show really good views cases. If you go into any of these, I was sitting in the transmission distribution one and it's amazing even in industry like transmission distribution which you think is a regulated industry, have been doing a tremendous amounts of stuff in terms of how they have been using the data or their PI system and improving operations and actually making things much more efficient for you and I to your point that there's so much of loss between the energy generated to finally reaching your light bulb at home and imagine them making significant improvements in that so that there's less loss of power when it comes to you. I mean it's more benefits for all of us. >> Oh, for sure. >> It's funny you mention the OSIsoft, is it known and I can see and understand that but this is the largest user conference they've had, they doubled the partner space that they've got. >> 3,000 people. >> People here so I think the recognition of, before I can get the insights from the data, I got to have it well-stored in that PI infrastructure, is growing among organizations, so that's why you see the growth in the user conference and once it's there, then we can kick in. The advanced analytics on top to go from the data collections stored and managed to the insights that drive better business outcomes. >> It's so much easier to get those efficiencies versus rip and replace or >> Leave the data where it is get your engineers' involved >> Leave the infrastructure. Fix the leak. 50 percent of my water is coming out that leak, it's crazy. All right, Sanket and Michael, we got to leave it there, thanks for sharing a few minutes with us. >> Sure, thanks for having us. >> Very much appreciate it. >> All right, I'm Jeff Frick, you're watching The Cube from OSIsoft 2018 Thanks for watching. (upbeat music)

>> Announcer: Live from the Computer History Museum in Mountain View, California. It's theCUBE covering DevNet Create 2018, brought to you by Cisco. (techy music playing) >> Hello, everyone, welcome back to theCUBE's exclusive coverage here in Silicon Valley. We're in Mountain View, California, for Cisco's DevNet Create. I'm here with Lauren Cooney, our analyst here with Wikibon, of course. Our next guest is Monica Houston, director of Hackster Live, Hackster IO, Hackster.io, open source hardware, really kind of creating a great community model. Really started from a great idea. Great to have you, thanks for coming, joining us. >> Thanks for having me. >> So, we're here at Cisco Live, so no better place to talk about hardware and software coming together, but first talk about how Hackster started, how it grew, where it is now today. >> Okay, so Hackster got started about four years ago here in San Francisco. The founders, Adam and Ben, they said they wanted to make a community for people that were interested in building open source hardware. Adam had actually come from starting his own hardware startup and realized that there were very few resources for people like him that wanted to build electronics, and so started a community. I got involved, started... We actually bought a DeLorean, drove it around the country and did hardware hack-a-thons in 12 different cities in the US. >> And so where's it today in terms of numbers, community members, and you're based in Seattle, is that right? >> I'm in Seattle. >> Okay. >> Yeah. >> So, what's the community look like, what's the numbers look like? >> There are half a million people on our site and 15,000 open source projects. >> John: Wow, awesome. >> Yeah. >> That is totally awesome, what projects do you see being the most popular on your site? >> Lots of home automation, home automation's a really popular topic. >> Lauren: Mm-hmm. >> We also get a lot of some pretty cool, like, music synthesizers, amplifiers. All kinds of stuff, yeah. >> That's great, now, say I'm like a... I, you know, have coded before but I'm not necessarily truly a developer. Like I'm a moonlighter, per se. >> Monica: Sure. (laughing) >> How could I get involved in this? >> Oh, man, there's tons of resources. So, actually on our site you can sort by difficulty. >> Lauren: Mm-hmm. >> So, if you want to find some beginner projects you can sort by difficulty and find only beginner projects. Also we have tutorials, so tutorials, getting started projects. >> Lauren: Mm-hmm. >> Like, so you buy an Arduino or you buy a particle board and you want to learn how to use it you can search for a getting started project on the site. >> Lauren: That's great. >> Yeah. >> How are you, like... So, you're at DevNet Create-- >> Monica: Yeah. >> With Cisco and what are you doing here? Like, what are you talking about, what are you really interested in? >> So, I have a project called Breadboard to PCB. I'm actually... So, I was a front-end web developer and then I got into all this, so I'm fairly new to it as well. I've been doing it for about six years. I'm not an electrical engineer. (laughing) I have to tell myself, but I'm doing a project called Breadboard to PCB. I made a PCB last year, sort of taught myself how to do that and realized it's actually not that hard and I want to spread that around to people and make them realize that they can build their own PCBs, too. >> That's terrific, that's awesome. Are you and Cisco, DevNet looking to share content or anything like that that might be cool? >> Yes, definitely. (laughing) >> Lauren: Okay. >> Yeah. >> All right, and is there any more you can tell us about that or is that still in the works? >> Still in the works, yeah, we offer... So, we have all these different partners, like Microsoft, Intel, hopefully Cisco as well-- >> Lauren: Mm-hmm. >> That do, they have, their hub is hosted on our site and people share their projects there with full instructions of a template. We actually go through and make sure everyone shares their code and their schematics. So, they're very well put together projects. >> Lauren: Great. >> Talk about some of the most exciting things you worked on, because one of the things I love about the open source culture is the creativity kind of comes out of nowhere. (laughing) We were just talking, before you came out, about my son, how he's been hacking his own thing. With this culture now you have so much online information. You go to YouTube, there's always a how-to. These communities have great resources. You guys got a robust community. So, there's always that natural, organic, "Whoa, look what this person did." >> Monica: Yeah. >> Can you share some stories around some killer things that happened. Not "killer," good things or just some things that are just creatively cool that you never would've thought would happen. >> Oh, man, so Allen Pan is a maker, I think he's based in LA. He has a YouTube channel, Allen Pan, and he did this really cool... I guess The Last Airbender is a popular movie and he did this flame activated, or punch activated flamethrower on his wrist. So, you try this at home. (laughing) Might be a little dangerous. >> What's his YouTube channel? >> I believe it's Allen Pan, is his name. >> So, there's some creative stuff, so people just tinkering around but there's also some serious hardware engineers. >> Monica: Mm-hmm. >> Any businesses starting out of this? Have you seen any, like, good ventures emerge? >> There's been a few things that I forgot about. There was a really cool watch that was Kickstarted that if you're a cyclist you can wear it and it tells you, like, which way to turn based on your GPS. >> John: Mm-hmm. >> There was some really nice Bluetooth, very elegant, like, Bluetooth controlled lights, that with different colors those are nice, yeah. >> So, what are some of the things you guys are doing in the community that you think's notable that you could share, people might be interested and like, how do you guys organize? There's some things that you guys do differently. What are some of the community activities that, you know, are standard. You know, the normal thing, you have meetups and whatnot, but like, how do you guys run your community, what are some of your guiding principles. Can you share how things work? >> So, we are always open, so you can go to our site and there's no, you know, there's no pay wall or barrier to view all of our content because our content comes from our community, and like, they're the ones that are... We're encouraging them to really document their work. Also, yeah, so we do hardware hack-a-thons where we try to make sure-- >> John: Yeah. >> Everyone's very... We're very beginner friendly, I guess. That's one of our goals is to make sure that people are coming from all different... You know, it's the artists that are making cool projects and-- >> So, when new people come in-- >> Mm-hmm. >> They get welcome letter, kind of community email haze or chat, all that stuff going on, all that's in place. >> We have a news feed, we have discussion, comments on the project that we moderate a bit, so yeah. >> So, Hackster.io. >> Hackster.io, yeah. >> All right, what's the coolest thing you guys are doing right now that you think we should know about? >> So, sort of related, actually this weekend I was at a workshop to learn how to make my own fire projects. (laughing) I like fire, (laughing) yeah. >> John: A pyromaniac community. I want the flamethrower fist thing. >> Yeah, I know. (laughing) >> Lauren: Over here is, yeah. >> I'm instantly like maybe on YouTube or something, I want that. That's a great party trick. >> I think it's great. >> Until something lights up. >> Right. (laughing) >> All right, so what are you doing here at Cisco? What's the focus here, obviously great culture they're building here. Very developer, not a lot of Cisco Kool-Aid being injected here, but much more of an outreach for Cisco, what's your focus here? >> This is all new for me, actually. So, I did not realize that this has got such a huge developer community and was really involved and like, this is a great conference. >> Lauren: That's true. >> People are so nice. >> Yeah, and the internet of things is a big hardware-- >> Yeah. >> Focused market. >> Yes, yeah. >> So, they've got all the software there. >> It's only getting bigger, yeah. >> Cool. >> Mm-hmm. >> Cool, all right, so what's new in Seattle? Give us an update on what you're doing. >> All right, it's still raining there. (laughing) >> That is actually very good to know. (laughing) >> You have Microsoft up there. >> Monica: Yeah. >> You have Amazon. >> Monica: Mm-hmm. >> University of Washington, so you have kind of a nice, kind of geek culture developing up there. So, yeah, good open source hardware vibe up there? >> Yeah. >> What's the community like in Seattle? >> Yeah, I run meetups, there's lots of people that come out to different hardware meetups and there are, like, a lot of new, cool hardware startups. Like for instance, Glowforge is a laser cutter that was Kickstarted recently. >> Lauren: Yep. >> There's some other really neat... DiGo is a home automation light switch. >> Lauren: Mm-hmm. >> Yeah, there's some pretty cool startups. >> So, if someone wants to join your community, what would you say to them if they're watching this video right now, hey. What are they, what's it like to join, what are they going to be... What's the vibe like, what are some of the things that are involved? What's the value for someone watching, that might want to join this, totally into tinkering with hardware? >> One thing is a great format to share your projects, and also to document your projects. Documentation is really important and I like to say that a project doesn't exist unless it's documented. (laughing) >> John: Yeah. >> So, documenting it and then we'll boost your project, we'll share it on our social media and it'll get lots of views. >> Yeah. >> Yeah. >> It's an open, it's a nerd culture. I mean, by the way, robotics is the hottest thing going on. You can't get involved, a lot of the younger generation are absolutely enamored with robotics, just at all levels. From, you know, you've got drones, which is super cool, right. Then you've got all the kind of stuff that's, it's all about hardware, hardware. >> Well, this is great, I'm on the site and I'm looking right now at the mind control drone. >> Monica: Oh, yeah. (laughing) >> That is, you know, my question is does that really work? Can I, you know, can I actually do something. You know, take this and learn from the site and actually build that? >> There are, and there are some developer, I guess it's EEG or EKG, EMG is another one, that you can really, you know, you can think left or think right and it will go left or right, it figures it out, yeah. >> That is so cool. >> Are people meeting up on the site and doing work together. Is it like a collaborative kind of hub going on there? >> There are some people that are doing that. Yeah, there was a few people on our site that were doing work on the, what was it... Elon Musk's thing, the... Hyperloop. >> John: Yeah. >> There's, like, the Hyperloop contest, and so a few people on our site were doing some work for that. >> Lauren: That's great. >> So, yeah, people are meeting there, yeah, for sure. >> Monica, great to have you here in theCUBE. Thanks for sharing about Hackster.io. We're going to check it out and thanks for the tip on the YouTube channel. We'll get the fire flamethrower. >> Yeah, make your own flamethrowers. >> John's going to be busy this weekend. (laughing) >> I'm a pyromaniac, I keep playing with matches all the time. So, thanks for coming on, I really appreciate it. >> Yeah, thank you. >> Hackster.io, we are theCUBE here live in Mountain View, California. Cisco DevNet Create, the Computer History Museum. We'll be right back with more after this short break. (techy music playing)