>>Okay we're here on the cube covering H. P. E. Accelerating next and with me is Rule Sister Mons, who was the head of it at the Netherlands Cancer Institute also known as NK I welcome rule. >>Thank you very much. Great to be here. >>Hey what can you tell us about the Netherlands Cancer Institute? Maybe you could talk about your core principles and and and also if you could weave in your specific areas of expertise. >>Yeah maybe first introduction to the National Cancer Institute. We are one of the top 10 comprehensive cancers in the world. And what we do is we combine a hospital for treating patients with cancer and research institute under one roof. So the discoveries we do we find within the research. We can easily bring them back to the clinic and and visa versa. So um we have about 750 researchers and about 3000 other employees, doctors, nurses and and my role is to facilitate them at their best with I. T. >>Got it. So I mean everybody talks about digital digital transformation to us that it all comes down to data. So curious how you collect and take advantage of medical data specifically to support NK eyes goals. Maybe some of the challenges that your organization faces with the amount of data, the speed of data coming in. Just the the complexities of data. How do you handle that? >>Yeah it's it's it's a challenge and uh what we we have we have a really a large amount of data so we produce uh terabytes today and we have stored now one petabyte of data at this moment. And it's uh the challenge is to reuse the data optimal for research and to share it with other institutions. So that needs to have a flexible infrastructure for that. So a fast really fast network big data storage environment. But the real challenge is not so much the I. T. But is more the quality of the data. So we have a lot of medical systems all producing those data and how do we combine them and you get the data fair. So findable accessible, interoperable and reusable for research purposes. So I think that's the main shell is the quality of the data. >>Very common themes that we hear from from other customers. I wonder if you could paint a picture of your environment and maybe you can share where HP solutions fit in what what value they bring to your organization's mission. >>Yeah I think it it brings a lot of flexibility. So what we did with HP. Es. That we we developed a software defined data center and then a virtual workplace for our researchers and doctors and that that's based on the HB infrastructure. And what we wanted to build is something that I expect the needs of doctors and nurses, but also the researchers and to kind of different blood groups, blood groups and with different needs. So, uh but we wanted to create one infrastructure because we wanted to make the connection between the hospital and research that's that's more important. So uh HPD helped helped us not only with the infrastructure itself, but also designing and the whole architecture of it. And for example, what we did is we bought a lot of hardware and and and the hardware is really doing his job between 9 to 5 Dennis, everything is working within, everyone is working with an institution, but all the other time in the evening and and nine hours and also the redundant environment we have for for our health care that doesn't do nothing of uh much more less uh in those uh dark hours. So, but we we created together with A V N H B and B M R, is that we we we call it Fidel today, compute by night. So we re use those uh those servers and those Gpu capacity for computational research jobs within the research. >>That's how you mentioned flexibility for this genius. And and so we're talking, you said a lot of hardware probably reliant, I think synergy Aruba networking is in there. How are you using this environment? Actually, the question really is when you think about NK eyes digital transformation, I mean, is this sort of the fundamental platform that you're using? Is it a maybe you could describe that? >>Yeah, it's the fundamental platform to work on. And what we see is that we have we have now everything in place for it. But the real challenge is, is the next steps we are in. So we have a software defined data center, we are cloud ready. So the next step is to make the connection to the cloud to give more automation to our researchers. So they don't have to wait a couple of weeks for I. T. To do it but they can do it themselves with a couple of clicks. So I think the basic is is we are really flexible and we have a lot of opportunities for automation for example. But the next step is to create that the business value really for for our employees. >>That's a great story and a very important mission. Really fascinating stuff. Thanks for sharing this with our audience today. Really appreciate your time. >>Thank you very much. >>Okay, this is Day Volonte with the cube stay right there for more great content. You're watching accelerating next from HP.

>>From around the globe. It's the cube with digital coverage of AWS reinvent 2020, sponsored by Intel and AWS. >>Welcome back to the cubes coverage of AWS reinvent 2020 I'm Lisa Martin. Joining me next is one of our cube alumni. Breton McMillan is back the director of us, federal for AWS. Right. It's great to see you glad that you're safe and well. >>Great. It's great to be back. Uh, I think last year when we did the cube, we were on the convention floor. It feels very different this year here at reinvent, it's gone virtual and yet it's still true to how reinvent always been. It's a learning conference and we're releasing a lot of new products and services for our customers. >>Yes. A lot of content, as you say, the one thing I think I would say about this reinvent, one of the things that's different, it's so quiet around us. Normally we're talking loudly over tens of thousands of people on the showroom floor, but great. That AWS is still able to connect in such an actually an even bigger way with its customers. So during Theresa Carlson's keynote, want to get your opinion on this or some info. She talked about the AWS open data sponsorship program, and that you guys are going to be hosting the national institutes of health, NIH sequence, read archive data, the biologist, and may former gets really excited about that. Talk to us about that because especially during the global health crisis that we're in, that sounds really promising >>Very much is I am so happy that we're working with NIH on this and multiple other initiatives. So the secret greed archive or SRA, essentially what it is, it's a very large data set of sequenced genomic data. And it's a wide variety of judge you gnomic data, and it's got a knowledge human genetic thing, but all life forms or all branches of life, um, is in a SRA to include viruses. And that's really important here during the pandemic. Um, it's one of the largest and oldest, um, gen sequence genomic data sets are out there and yet it's very modern. It has been designed for next generation sequencing. So it's growing, it's modern and it's well used. It's one of the more important ones that it's out there. One of the reasons this is so important is that we know to find cures for what a human ailments and disease and death, but by studying the gem genomic code, we can come up with the answers of these or the scientists can come up with answer for that. And that's what Amazon is doing is we're putting in the hands of the scientists, the tools so that they can help cure heart disease and diabetes and cancer and, um, depression and yes, even, um, uh, viruses that can cause pandemics. >>So making this data, sorry, I'm just going to making this data available to those scientists. Worldwide is incredibly important. Talk to us about that. >>Yeah, it is. And so, um, within NIH, we're working with, um, the, um, NCBI when you're dealing with NIH, there's a lot of acronyms, uh, and uh, at NIH, it's the national center for, um, file type technology information. And so we're working with them to make this available as an open data set. Why, why this is important is it's all about increasing the speed for scientific discovery. I personally think that in the fullness of time, the scientists will come up with cures for just about all of the human ailments that are out there. And it's our job at AWS to put into the hands of the scientists, the tools they need to make things happen quickly or in our lifetime. And I'm really excited to be working with NIH on that. When we start talking about it, there's multiple things. The scientists needs. One is access to these data sets and SRA. >>It's a very large data set. It's 45 petabytes and it's growing. I personally believe that it's going to double every year, year and a half. So it's a very large data set and it's hard to move that data around. It's so much easier if you just go into the cloud, compute against it and do your research there in the cloud. And so it's super important. 45 petabytes, give you an idea if it were all human data, that's equivalent to have a seven and a half million people or put another way 90% of everybody living in New York city. So that's how big this is. But then also what AWS is doing is we're bringing compute. So in the cloud, you can scale up your compute, scale it down, and then kind of the third they're. The third leg of the tool of the stool is giving the scientists easy access to the specialized tool sets they need. >>And we're doing that in a few different ways. One that the people would design these toolsets design a lot of them on AWS, but then we also make them available through something called AWS marketplace. So they can just go into marketplace, get a catalog, go in there and say, I want to launch this resolve work and launches the infrastructure underneath. And it speeds the ability for those scientists to come up with the cures that they need. So SRA is stored in Amazon S3, which is a very popular object store, not just in the scientific community, but virtually every industry uses S3. And by making this available on these public data sets, we're giving the scientists the ability to speed up their research. >>One of the things that Springs jumps out to me too, is it's in addition to enabling them to speed up research, it's also facilitating collaboration globally because now you've got the cloud to drive all of this, which allows researchers and completely different parts of the world to be working together almost in real time. So I can imagine the incredible power that this is going to, to provide to that community. So I have to ask you though, you talked about this being all life forms, including viruses COVID-19, what are some of the things that you think we can see? I expect this to facilitate. Yeah. >>So earlier in the year we took the, um, uh, genetic code or NIH took the genetic code and they, um, put it in an SRA like format and that's now available on AWS and, and here's, what's great about it is that you can now make it so anybody in the world can go to this open data set and start doing their research. One of our goals here is build back to a democratization of research. So it used to be that, um, get, for example, the very first, um, vaccine that came out was a small part. It's a vaccine that was done by our rural country doctor using essentially test tubes in a microscope. It's gotten hard to do that because data sets are so large, you need so much computer by using the power of the cloud. We've really democratized it and now anybody can do it. So for example, um, with the SRE data set that was done by NIH, um, organizations like the university of British Columbia, their, um, cloud innovation center is, um, doing research. And so what they've done is they've scanned, they, um, SRA database think about it. They scanned out 11 million entries for, uh, coronavirus sequencing. And that's really hard to do in a typical on-premise data center. Who's relatively easy to do on AWS. So by making this available, we can have a larger number of scientists working on the problems that we need to have solved. >>Well, and as the, as we all know in the U S operation warp speed, that warp speed alone term really signifies how quickly we all need this to be progressing forward. But this is not the first partnership that AWS has had with the NIH. Talk to me about what you guys, what some of the other things are that you're doing together. >>We've been working with NIH for a very long time. Um, back in 2012, we worked with NIH on, um, which was called the a thousand genome data set. This is another really important, um, data set and it's a large number of, uh, against sequence human genomes. And we moved that into, again, an open dataset on AWS and what's happened in the last eight years is many scientists have been able to compute about on it. And the other, the wonderful power of the cloud is over time. We continue to bring out tools to make it easier for people to work. So what they're not they're computing using our, um, our instance types. We call it elastic cloud computing. whether they're doing that, or they were doing some high performance computing using, um, uh, EMR elastic MapReduce, they can do that. And then we've brought up new things that really take it to the next layer, like level like, uh, Amazon SageMaker. >>And this is a, um, uh, makes it really easy for, um, the scientists to launch machine learning algorithms on AWS. So we've done the thousand genome, uh, dataset. Um, there's a number of other areas within NIH that we've been working on. So for example, um, over at national cancer Institute, we've been providing some expert guidance on best practices to how, how you can architect and work on these COVID related workloads. Um, NIH does things with, um, collaboration with many different universities, um, over 2,500, um, academic institutions. And, um, and they do that through grants. And so we've been working with doc office of director and they run their grant management applications in the RFA on AWS, and that allows it to scale up and to work very efficiently. Um, and then we entered in with, um, uh, NIH into this program called strides strides as a program for knowing NIH, but also all these other institutions that work within NIH to use the power of the cloud use commercial cloud for scientific discovery. And when we started that back in July of 2018, long before COVID happened, it was so great that we had that up and running because now we're able to help them out through the strides program. >>Right. Can you imagine if, uh, let's not even go there? I was going to say, um, but so, okay. So the SRA data is available through the AWS open data sponsorship program. You talked about strides. What are some of the other ways that AWS system? >>Yeah, no. So strides, uh, is, uh, you know, wide ranging through multiple different institutes. So, um, for example, over at, uh, the national heart lung and blood Institute, uh, do di NHL BI. I said, there's a lot of acronyms and I gel BI. Um, they've been working on, um, harmonizing, uh, genomic data. And so working with the university of Michigan, they've been analyzing through a program that they call top of med. Um, we've also been working with a NIH on, um, establishing best practices, making sure everything's secure. So we've been providing, um, AWS professional services that are showing them how to do this. So one portion of strides is getting the right data set and the right compute in the right tools, in the hands of the scientists. The other areas that we've been working on is making sure the scientists know how to use it. And so we've been developing these cloud learning pathways, and we started this quite a while back, and it's been so helpful here during the code. So, um, scientists can now go on and they can do self-paced online courses, which we've been really helping here during the, during the pandemic. And they can learn how to maximize their use of cloud technologies through these pathways that we've developed for them. >>Well, not education is imperative. I mean, there, you think about all of the knowledge that they have with within their scientific discipline and being able to leverage technology in a way that's easy is absolutely imperative to the timing. So, so, um, let's talk about other data sets that are available. So you've got the SRA is available. Uh, what are their data sets are available through this program? >>What about along a wide range of data sets that we're, um, uh, doing open data sets and in general, um, these data sets are, um, improving the human condition or improving the, um, the world in which we live in. And so, um, I've talked about a few things. There's a few more, uh, things. So for example, um, there's the cancer genomic Atlas that we've been working with, um, national cancer Institute, as well as the national human genomic research Institute. And, um, that's a very important data set that being computed against, um, uh, throughout the world, uh, commonly within the scientific community, that data set is called TCGA. Um, then we also have some, uh, uh, datasets are focused on certain groups. So for example, kids first is a data set. That's looking at a lot of the, um, challenges, uh, in diseases that kids get every kind of thing from very rare pediatric cancer as to heart defects, et cetera. >>And so we're working with them, but it's not just in the, um, uh, medical side. We have open data sets, um, with, uh, for example, uh, NOAA national ocean open national oceanic and atmospheric administration, um, to understand what's happening better with climate change and to slow the rate of climate change within the department of interior, they have a Landsat database that is looking at pictures of their birth cell, like pictures of the earth, so we can better understand the MCO world we live in. Uh, similarly, uh, NASA has, um, a lot of data that we put out there and, um, over in the department of energy, uh, there's data sets there, um, that we're researching against, or that the scientists are researching against to make sure that we have better clean, renewable energy sources, but it's not just government agencies that we work with when we find a dataset that's important. >>We also work with, um, nonprofit organizations, nonprofit organizations are also in, they're not flush with cash and they're trying to make every dollar work. And so we've worked with them, um, organizations like the child mind Institute or the Allen Institute for brain science. And these are largely like neuro imaging, um, data. And we made that available, um, via, um, our open data set, um, program. So there's a wide range of things that we're doing. And what's great about it is when we do it, you democratize science and you allowed many, many more science scientists to work on these problems. They're so critical for us. >>The availability is, is incredible, but also the, the breadth and depth of what you just spoke. It's not just government, for example, you've got about 30 seconds left. I'm going to ask you to summarize some of the announcements that you think are really, really critical for federal customers to be paying attention to from reinvent 2020. >>Yeah. So, um, one of the things that these federal government customers have been coming to us on is they've had to have new ways to communicate with their customer, with the public. And so we have a product that we've had for a while called on AWS connect, and it's been used very extensively throughout government customers. And it's used in industry too. We've had a number of, um, of announcements this weekend. Jasmine made multiple announcements on enhancement, say AWS connect or additional services, everything from helping to verify that that's the right person from AWS connect ID to making sure that that customer's gets a good customer experience to connect wisdom or making sure that the managers of these call centers can manage the call centers better. And so I'm really excited that we're putting in the hands of both government and industry, a cloud based solution to make their connections to the public better. >>It's all about connections these days, but I wish we had more time, cause I know we can unpack so much more with you, but thank you for joining me on the queue today, sharing some of the insights, some of the impacts and availability that AWS is enabling the scientific and other federal communities. It's incredibly important. And we appreciate your time. Thank you, Lisa, for Brett McMillan. I'm Lisa Martin. You're watching the cubes coverage of AWS reinvent 2020.