 Live from Orlando, Florida, it's theCUBE. Covering Pentaho World 2017. Brought to you by Hitachi Ventara. Welcome back to theCUBE's live coverage of Pentaho World, brought to you by Hitachi Ventara. I'm your host, Rebecca Knight, along with my co-host, Jim Kobielus. We are joined by Gio Thomas. He is the director of IT at Benefit Science, a healthcare insurance analytics company. Thanks so much for coming on theCUBE, Gio. Thank you, thanks for having me. So Benefit Science is a company launched out of MIT. Tell our viewers a little bit more about the company. Okay, so Benefit Science is a healthcare data analytical company, which co-founded by MIT Alumni's, Dr. Dimitri's and Dr. Stephen Seafall, so forth. And we have one more partner. And we do data analytics on the healthcare side and we work with employers and the brokers to analyze the data and give them dashboards and workbooks and so that's what we mainly do. And we, yeah. So as you said, you work with employers to save them healthcare dollars? I mean, can you get into the nitty gritty a little bit? That's exactly right, yeah. So what we do is we empower employers to manage their employee benefits mainly and providing them that analytical tools and other optimization tools. And we give them a very fine, clear picture of how these plans are performing and how they can optimize their plans in the near future by giving plan optimization tools and risk or algorithms and things like that. You provide this as a managed service for your clients or do you provide basically licensed software that helps them do this for themselves? Yeah, so from their own premises. So we are a cloud platform and we provide our platform as a service for our clients. So we get the data from them and we provide data analytical tool by mashing up this data and they use our platform to see those reports and insights and things like that. So healthcare data is a really special kind of complicated when it comes to data because there's so many security and privacy issues related to it. How do you go about managing this kind of data? Yeah, it's healthcare data is very complex as you know, very huge and we can't expect what comes next. And there are a lot of regulations and there are a lot of security issues. So we take all this with utmost priority. So our company is a SOC1 SOC2 certified company and which covers a lot of regulations by itself and our employers, benefit science employees are really very much aware of these HIPAA rules and they all are certified and we have lots of internal and external audits and regulations throughout the place. So that would cover all these compliance issues mainly. From an operational standpoint, how are you managing the data day in, day out? Do you provide a data warehouse and within which you load it and then from which you do the analysis? Or it's a sense for how you've architected your environment and then where Pentaho plays into the overall picture. Yeah, so we take the data, once we get the data, we mash up the data. So how we do this, we use Pentaho as an end to end tool because it gives us a very standardized methodologies to process this data. So we de-identify the PHA data, we sample it, scramble it, and then we do the development. And once the development is done and nobody tests any of those PDA jobs or the jobs which we created with Pentaho and we run this in a very secure environment and which pulls all this transformed data into a data analytical platform. When you say scramble in this kind of thing, you're referring to masking and anonymizing the data? Correct. So okay, that's, I assume, you tell me, that's required by HIPAA that you do it that way? Okay, yes. Yes, good. So we don't take all the data for the development, we take only the sample data and then we scramble it and we identify all this information. So what kind of results have you seen in your company since using Pentaho? So I started in like almost one year back and when we started, we had like 20 tenants. Now we have 200 tenants. So that's a summary of the result what I'm seeing because Pentaho gives us a lot of flexibility to standardize and make proper checks and balances throughout the data pipeline and we had created a very huge test framework which can run automatically. So all these things would benefit us to board a client because right now onboarding a client would take like less than a week. When you say a test for a minute, it could be automated, what sort of test are you referring to? So we create test scripts and we created a test suite framework by using Pentaho jobs and we schedule that and that test suite what we do is every whenever any tenant comes in, developers can create a number of test cases and plug that in. So it is growing and that will run automatically along with the PDA jobs. So that gives us a number of outputs and checks and balances and depending on this results, we board the client. So yeah. Saving healthcare dollars, spending healthcare dollars wisely, this is really part of the national conversation. How much does benefit science really feel a responsibility to weigh in on these issues? I mean, we were hearing, we heard a lot from the CEO this morning about how Pentaho really views its guiding principles as doing good in the world and bettering society. The double bottom line. The double bottom line, exactly. Very true, very true because as a benefit science company, our vision or our motto is not to just build some software and give to customers and get some money. Our vision is to help people or employers to reduce the healthcare cost. So our data scientists build this great plan optimization tools or RISCO tools to provide employers to look at, okay, these are the large claimant details which we might have to go and find out the reasons and work with them to reduce the cost. So we are giving all these tools for them. And another thing is the data ad hoc analyzer. Our users love it because we provided a simplified cube for them to drag and drop and create the reports and they can easily drag a couple of data elements and come up with, okay, these are the paid amounts which we paid last month and this has to go down. So they can come up with their own strategies to make it down at least for the next year in enrollment. In terms of users being able on a self-service basis to find their views and their reports. Do you take that intelligence that you gain from users and then use that, bring that back into the basic service in terms of adjusting the data model, the set of canned reports or dashboards you provide? What do you do in that regard? Yeah, so we have a custom insight reports which would give a pretty good idea about what this data meant to be for the customers like drug dashboards or large claimants or quality measures or things like that. We also have another data science group works on this artificial AI tools or machine learning algorithms to provide more predictive analysis. So that would give users to a different perspective of okay, if we do this, we can reduce the cost. Is that WECA or? No, we are using predictive. So that's another thing I want to go back and tell them, okay there is a WECA here, we probably have to start using it. So right now we are using R and Python and there's something called Groovy. So that's what we use. What are some challenges that you're facing right now? What is keeping you up at night and what do you want the next versions of Pentaho to solve for you? So I'm a director of IT, so I care about IT more than the business. So my challenge is always how I can board more clients within a short span of time. The scalability, the security, how we can make it compliant. So I was listening to that ATO, what are the new things coming in ATO? One of the main thing I was looking at is the scalability, that is, there is something called Worker Nord that's got announced in ATO, which you can scale as a docker and you can spin off as many dockers as you want and it will work by itself. That's fantastic, I'm really looking forward to get that scalability into our system. So you're seeing your IT environment, you're focused now more and more on a cloud-native environment that takes the application functionality and wraps it as containers? Okay, so that's where you're going and then you're saying that, I don't know what to put words to your mouth, that's what you're doing is consistent with where Pentaho is going with their overall product platform, right? Right, yeah. So we are hosting in AWS Cloud and with the Pentaho. So Pentaho is also going into that direction and makes me very happy because we are really looking forward to get that working in the cloud. And the thing is, the Worker Nord, what they're talking about is what we were thinking of implementing on our own. So now they're on Worker Nord and which we can just take and put it there. So that's very good news. I wanted to ask you about the talent shortage in technology because that is something that the CEO talked about, Karen Perlich talked about too, is that this real dearth of talent in data science. There was a piece in The New York Times just the other day that talked about how data scientists that just a PhD can come out and make half a million dollars in Silicon Valley. What do you think will be the real change and that will get more and more graduates into this field? It seems as though the money should be enticement enough, really. I mean. That's a million dollar question though. But yeah, even we are in the same boat. You're a Massachusetts based company. It should be. Even with that, we are finding a lot of difficulties to get some good data scientists because the moment you passed out as a data scientist, they're asking like half a million. So. Literally, I saw an article the other day, a good data scientist in Silicon Valley can fetch upwards of a half a million per year. Imagine in other regions of Massachusetts has no shortage of educated, smart people. But still. But still. So the moment they have that label, then yes. So these tools would help. And building that artificial intelligence on top of these tools would help definitely to have some sort of not have, not depending on data scientists so much that even others can do those. So you might not need the talent in a way. Yeah. So I'm looking forward to that. Because I was listening to your session in the morning and I'm very impressed with that because that's where I'm also trying to see where the world is heading to. Right. So you make recommendations to your clients about how they should structure their healthcare insurance plans for employees. Do you have a capability right now within Benefit Science to basically embed sort of a recommendation engine of that sort to help advisors on your staff to work with clients to recommend the right set of options or approaches pulling from the data? Is that already there? Yeah, it's already there. Yeah. So we provide the recommendations for clients by using these algorithms. So we have this plan optimization tool which would give you, okay, if you do such and such things, this is going to go down in the next year. Or there is a plan design data. So whenever an enrollment happens, the main thing they look at is what plan they have to select for their set of employees. So every case is unique. So we put a lot of historical data information and we put those machine learning algorithms in there. And then we come up with, so we train that model with all this data and we predict for each tenant. Great. So yeah. Right. So we have that right now. Gio, thanks so much for coming on theCUBE. It's been really fun talking to you. Thanks for having me. I'm Rebecca Knight for Jim Kobielus. We will have more from theCUBE's live coverage of Pentaho World just after this.