 Live from Las Vegas, it's theCUBE! Covering AWS re-invent 2019. Brought to you by Amazon Web Services and Intel, along with its ecosystem partners. Hey, welcome back to theCUBE's coverage of AWS 19 from Las Vegas. This is day two of our coverage of three days, two sets, lots of CUBE content. Lisa Martin here with Justin Warren, founder and chief analyst of Pivot 9. Justin and I are joined by a couple of guests new to theCUBE. We've got David Peister next to me, global head of sales for Io Tahoe, welcome. Yeah, glad to be here. Eddie Edwards, what a cool name. Global data services director from Direct Energy. Welcome Eddie. Hi, thank you. Okay, so David, I know we had somebody from Io Tahoe on yesterday, but I'd love for you to give our audience an overview of Io Tahoe, and then you got to tell us what the name means. Oh, okay. Well, Dave Peister, Io Tahoe, thanks, it's a wonderful event here at AWS, and excited to be here. Io Tahoe, we're located in downtown Wall Street, New York. And Io Tahoe, well, there's a lot of different meanings, but mainly Tahoe for Data Lake, input, output into the lake is how it was originally meant. But a little background on Io Tahoe, we are, 2014, we started in Stealth, came out of Stealth in 2017 with two signature clients, one you're going to hear from in a moment, Direct Energy, the other one GE, and we'll speak to those in just a moment. Io Tahoe takes a unique approach. We have nine machine learning algorithms, 14 future sets that interrogates the data at the data level. We go past metadata, so solving that really difficult data challenge. And I'm going to let Eddie describe some of the use cases that were around data migration, PII discovery, and so over to you. Thank you. First tell us a little bit about Direct Energy, what you were, you're located, and what you guys do, and how data is absolutely critical to your business. Yeah, sure. So Direct Energy, well, it's the largest, residential energy supplier in the US, around 5,000 employees. Lots of this has come from acquisitions. So as you can imagine, we have a vast amount of data that we need to manage. So currently I've got just under 1,700 applications in my portfolio, and a lot of the challenges we get are around the cost, driving down cost to serve, so we can pass that back on to our consumers. And the challenge that we've had is, how best to gain that understanding where IOTA hole came into play. It was mainly around our ability to use the product quickly for being able to connect to our existing sources, to discover the data, but then to catalog that information, to start applying the rules around whether it be legislation like GDPR, or we get a lot of cases where there's a difference between the state's understandings and definitions, so the product gives us the ability to bring a common approach to that information. Good success story would be about three months ago, we took 13 applications for our North America home business. We were able to run it through the product within a week, and that gave us the information to then consolidate the state downwards, working with our business colleagues to identify all the data redundancy, the archival retention rules, and bring more meaning to the data, and actually improve ourselves opportunities by highlighting that rich information that was not known previously. Yeah, so you mentioned that you've grown through acquisition. One thing that people tend to underestimate around IT is that it's not a homogeneous environment, it's heterogeneous. As soon as you buy another company, you've got another silo, you've got another data set, you've got something else. So walk us through how IOTA who actually deals with that very disparate set of data that you've no doubt inherited from just acquiring all of these different companies. Yeah, so exactly right. Every time we acquire an organization, they would have various different applications that were running in the estate, whether it be an old Oracle, SAP, SQL type environment. What we're able to do is use the product to plug in and then profile to understand what insight knowledge they have around their customer base and how we can then bring that in to build up a single view and offer additional products, value-adding products or rewards for customers, whether that be on our HVAC side, our heating, ventilation and aircon unit, which again we have 4,600 engineers in that space. So it's opening up new opportunities and territories to us. Go ahead. As I say additionally to that, we're across multiple sectors, but the problem, Death by Excel, was in the financial services. We're located in Wall Street, as I mentioned, and this problem of legacy disparate data sources and understanding and knowing your data was a common problem. Banks were just throwing people with the problem. So his use case with 1,700 applications, a lot of them legacy, it fits right into what we do. And cataloging is a, he mentioned we catalog, with that discover and search engine that we have, we enable search across the enterprise, but discovery, we auto-tag and auto-classify the sensitive data into the catalog automatically, and that's a key part of what we do, and yeah. Was that, Dave, something, I'm thinking of differentiation, wanting to know what is unique about iOtahoe, what was the opportunity that you guys saw, but is the cataloging of the sensitive information one of the key things that makes it different? We enable data governance, so it's not just sensitive information, we catalog the entire data set, multiple data sets, and what makes us, what differentiates us is that the machine learning, we interrogate and brute force the data. So every single, so metadata beyond, so billion rows, 100,000 columns, large, complex data sets, we interrogate every field value, and we tell you, well this looks like a phone number, this looks like an address, this looks like a first name, this looks like a last name, and we tag that to the catalog, and then anything that's sensitive in nature will color code it, red, green, highly sensitive, sensitive, so that's our big differentiator. So it's that like 100% visibility into the granularity of what is in this data? Yes, and that's one of the issues is that we're here at AWS, we're finding a lot of folks are wanting to go to the cloud, but they can't get access to the data, they don't know their data, they don't understand it, and so we're that bridge, we're a key strategic partner for AWS, and we're excited about the opportunity that's come about in the last six months with AWS, because we're going to be that key piece for migration to the cloud. So the Data Lake, I love the name, Iow Chahou, but in your opinion, you know you can hear so many different things about Data Lake, data's turning into data swamp, is there's still a lot of value in Data Lakes that customers just like you were saying before, they just don't know what they have. Well what's interesting, and this is a good transition to one of our other clients, but and I just want to make a note that we actually started in the relational world, so we're RWMS, we're across heterogeneous environment, but Tahoe does have more to do with Lake, but at a time, a few years back, everybody was just dumping data into the lake, they didn't understand what was in there, and it's created in this era of privacy a big issue, and Comcast had this problem, the large teradata instance just dumping into the lake, not understanding data flows, how their data's flowing, not understanding what's in the lake sensitivity wise, and they want to start, you know, they want to enable BI, they want to start doing analytics, but they got to understand and know the data, right? So for Comcast, we enabled data ops for them, automatically with our machine learning, so that was one of the use cases, and then they put the information in and we integrated it with Apache Atlas, and they have a large AWS instance, and they're able to then better govern their data, and GE Digital, one other customer, very complex use case around their data, 36 ERPs being migrated to one virtual ERP in the lake, and think about finance data, how difficult that is to manage and understand, so we were a key piece in helping that migration happen in weeks rather than months. So David, you mentioned cloud, clearly we're at a cloud show, but you mentioned knowing your data, one of the aspects of that cloud is that it moves fast, and it's at a much bigger scale than what we've been used to, so I'm interested, maybe Eddie, you can fill us in here as well, about the use of a tool to help you know your data when we're not creating any less data, there's just more and more data, so at this speed and at this scale, how important is it that you actually have tooling to provide to the humans who have to go and operate on all of this data? Building on what David was saying around the speed and the agility side, all our information now for our North America home business is in AWS, all an NS3 bucket. We are already starting work with AWS Connect and the call center side, being able to stream that information through, so we're getting to the point now as an organization where we're able to profile the data real time and take that information, but predict what the customer's going to do as part of the machine learning side, so we're starting to trial where we will interject into a call to say, well, you know, a customer might be on your digital site trying to do a journey, you can see the challenges around data, and you could then go in with a chat using say the new AWS chat that's just coming through at the moment, so great opportunities. I'm hearing, sorry Eddie, is the opportunity to leverage the insights into the data to deliver more, you mentioned like customer rewards or more personalized experiences or a call center agent knowing this is the problem that this customer is experiencing, this, we have tried X, Y and Z to resolve or this customer is loyal, they pay their bills on time, they should be eligible for some sort of reward program. I think as consumers that I think Amazon.com has created this demanding consumer that we expect you to know us, we expect you to serve us up things that you think we want, talk to me about the opportunity that IOTI is giving your business to be able to delight customers in ways that you probably couldn't even have predicted. Well, David touched on the tagging earlier, you know, so by understanding the data that's coming through, being able to use the data flow technology and categorizing, we're able then to link it in with the wider estate. So David mentioned Comcast around 36 ERP, you know, we've just gone through the same in other parts of our organization, we're driving that additional level of value, turning it away from being a manually labor intensive task. So I used to have, you know, 20 architects that daily go through trying to build and understanding the relationship. I do not need that now. I just have a couple of people that are able to take the outputs and then be able to validate the information using the products. And I'd like to add there's just so much, you mentioned customer 360 example at a call center. There's so much data ops that has to happen to make that happen. And that's the most, you know, difficult challenge to solve and that's where we come in after you catalog the data, I just want to touch on this, we enable search for the enterprise. So you've now connected to 5,100, 1,500 sources with our software. Now you've cataloged it, you profiled it. Now you can search. Karen, Kim, Kim Smith. So your engineers, your architect, your data stewards, your influencers, your business analysts, business folks can now search anything they want and find anything sensitive, find that person, find an invoice. And that helps enable what you mentioned, the customer 360. Right, that 360, but I can also, what I'm hearing is it has the potential to enable a better relationship between IT and the business. Absolutely, it brings those both together because they're so siloed in this day and age. Your data is siloed and your business is siloed in the different business units. So this helps exactly collaborate crowdsource, bring it all together to one platform. And how many, so 1,700 applications, how many you mentioned that 36 are so ERPs, what percentage, if you can guess, have you been able to reduce duplicate, triplicate, et cetera applications and what are some of the overarching business benefits that direct energy is achieving? So in terms of the direct synergy side, we're just at the beginning of that journey. We're about four months in, but we've already decommissioned 12 of the applications and we're starting to move out to the wider side. In terms of benefits, ROI probably around 300% at the moment. And in a few, 300% ROI in just a few months? Yes, just another, you know, you've got some of the basic savings around the storage side. We're also getting large savings from some of the existing support agreements that we have in place. David touched on data ops. I've been able to reduce the amount of people that are required to support the team. There is now a more common understanding within the organization. And I've managed to turn it more into a self-care opportunity with the business operations by pushing the line from being a technical problem to a business challenge. And at the end of the day, they're the experts. They understand the data better than any IT fault that are set in a corner, right? So... I've got to ask you one more question, Eddie. Yeah, sure. What gave you the confidence that IoTahoe was the right solution for you? Purely down to the open source side. So we come from a, you know, I've been using IoTahoe probably for about two years in parts of the organization. We were very early adopters on other technologies in the open source market. And it was just the ability to, on the proof of concepts, be able to turn it around. Items where you'll go to a traditional vendor, which would take a few months, large business cases, didn't need any of that. We were able to show results within 24, 48 hours. And that buys the confidence. And I'm sure David would take the challenge of being able to plug in some data sets and show you the data. Cool stuff, guys. Well, thank you for sharing with us what you guys are doing in IoTahoe, keeping that data lake blue, and the successes that you're achieving in such a short time at Direct Energy. Appreciate your time, guys. Thank you for having us on. Our pleasure. No your data. Exactly, no your data, for my guests and my co-host, Justin Warren. I'm Lisa Martin. I'm going to go off and learn my data now. You've been watching theCUBE at AWS Reinvent 19. Thanks for watching.