>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 >>sponsored by >>Intel and AWS. Yeah, Welcome back to the cubes. Ongoing coverage of aws reinvent virtual the Cuba has gone virtual to. We're gonna talk about machine intelligence, cloud and transformation in healthcare. An industry that is rapidly evolving and reinventing itself to provide better quality care faster and more accurate diagnoses. And this has to be done at lower cost. And with me to talk about This is Dr Taha. Awesome. Who? Who is the director of machine learning at Amazon Web services? Doctor, good to see you again. Thanks for coming on. >>Thank you so much. Good to see Dave. >>Yeah, last time we talked, I think it was a couple of years ago. We remember we were talking about Amazon. Comprehend medical. And, of course, you've been so called so called raising the bar, so to speak, Over the past 24 months, you made some announcements today, including Amazon Health Lake, which we're gonna talk about. Tell us about it. >>Well, we're really excited about eso our customers. Amazon Half Lake, a new hip eligible service for health care providers health insurance companies and pharmaceutical companies to securely store, transform Aquarian, analyze health data in the cloud at petabytes scale, a Amazon health lake uses machine learning models trained to automatically understand context and extract meaningful data from medical data from raw, disparate information such as medications, procedures, Um, and diagnosis. Um Therefore, revolutionizing a process that was traditionally manual Arab prone and highly costly requires a lot of expertise on teams within these organizations. What healthcare Catholic does is it tags and indexes every piece of information on then structure in an open standard. The fire standard, or that's the fast healthcare interoperability resource, is in order to provide a complete view 360 degree view of each patient in a consistent way so you'll be able to curry and share that data securely. It also integrates with other machine learning services and a lot of services that AWS offers, such as Amazon Quicksight or Amazon sage maker. In order to visualize and understand the relationships in the data identify trends, Andi also make predictions. The other great benefit is since the Amazon health lake automatically structures all the health care organizations data into open standard. The fire industry format. The information now can be easily and securely shared between systems. Health systems onda with third party applications. So eso providers, health care providers will will enjoy the ability to collaborate more effectively with each other but also allowing patients and federal access to their medical information. >>I think now, so one of things that people are gonna ask is Okay, wait a minute. Hip eligible Is that like cable ready or HD ready? And but people need to understand that it's a shared responsibility. But you can't come out of the box and be HIPPA compliant there a number of things and processes, uh, that that your customer has to do. Maybe you could explain that a little >>bit. Absolutely. I mean, in practice a little bit. This is a very, very important thing, and and it's something that we really fully baked into the service and how we built Also the service, especially dealing with health care information. First off, AWS, as you know, is vigilant about customers, privacy and security. It is job zero for us. Your data and Health Lake is secure, compliant, and auditable data version is enabled to protect um, the data against any accident collision, for example, and per fire sophistication. If you are to delete one piece of data, it will be version it will be on Lee. Hidden from analysis is a result not believed from the service. So your dad is always encrypted on by using your own customer. Manage key in a keys in a single tenant. Architectures is another added benefit to provide the additional level of protection when the data is access and search for example, every time inquiry a value, for example, someone's glucose level if the data is encrypted and decrypted and and and and so on and so forth. So, additionally, this system in a single tenant architectures so that that way the data, uh, the key. The same key is not shared across multiple customers. So you're saying full ownership and control of your data along with the ability to encrypt, protect move, deleted in alignment with organization, security and policies. Now a little bit about the hip eligibility. It's a term that AWS uses eso for customers storing protected health information or P h. I A. DBS by its business associate agreement on also Business Associate amendment require customers to encrypt data addressed in transit when they're using area services. There are over 100 services today. They're hip eligible, including the Amazon. Health like this is very important, especially for, uh enabling discovered entities and their business associates subject to HIPAA regulations, and is be able to kind of and this shared model between what a the best protection and services and how it can process and store and managed ph I. But there's additional level of compliance is required on the on the customer side, um, about you know, anywhere from physical security thio how each application can be built, which is no different than how you manage it. For example, today in your own that data center, what not? But this is why many cats, growing number of health care providers, um, players as well as I, because professionals are using AWS utility based cloud services today to process, store and transmit pH. I. >>So tell us more about who was gonna benefit from this new capability, what types of organizations and would be some of the outcomes for for for patients, >>absolutely every healthcare provider today, or a payer like a health insurance company or a life. Science companies such as Pharma Company is just trying to solve the problem of organizing instruction their data. Because if you do, you make better sense of this information from better patient support decisions. Design better clinical trials, operate more efficiently, understand population health trends on be able them to share that that security. It's really all starts with making sense of that of that data. And those are the ultimate customers that we're trying to empower with the Amazon Amazon Health Lake. Um, >>well, And of course, there's downstream benefits for the patient. Absolutely. That's ultimately what we're trying to get to. I mean, absolutely. I mean, I set up front. I mean, it's it's everybody you know, feels the pain of high health care costs. A lot of times you're trying to get to see a doctor, and it it takes a long time now, especially with with covitz so and much of this, oftentimes it's even hard to get access to your own data s. So I think you're really trying to attack that problem. Aren't >>you absolutely give you a couple of examples like I mean, today, the most widely used clinical models, uh, in practice to predict. Let's say someone's disease risk lack personalization. Um, it's you and I can be lumped in the same in the same bucket, for example, based on a few attributes that common, UM, data elements or data points, which is problematic also because the resulting models produce are imprecise. However, if you look at an individual's medical records, for example, you know a diabetic type two diabetic patients there, if you look at the entire history and from all this information coming to them, whether it's doctor knows medication dosages, which line of treatment the second line treatment, uh, continuous monitoring of glucose and that sort of thing is over hundreds. You know, there are hundreds of thousands of data points in their entire medical history, but none of this is used today. At the point of care on. You want all this information to be organized, aggregated, structured in a way that you will be able to build even better models easily queried this information, aan den observed the health of the individual in comparison with the rest of the population because at that point you'll be able to make those personalized decisions and then also for patient engagement with the health lake ability to now emit data back on dshea air securely the a p i s that conform to the fire standard. So third party applications can be built also, um, Thio provide the access whether that's for analytics or digital health application, for example, a patient accident, that information all that is very, very, very important. Because ultimately you wanna, um, get at better care of these these populations better. In Roma, clinical trials reduce duplicative tests and waste and health care systems. All that comes when you have your entire information available in a way that structured and normalize on be able to Korean and analyze andan the seamless integration between the health lake and the arrest of the services like Amazon sage maker. You can really start to understand relationships and meaning of the information, build better, better decision support models and predictive models at the individual on a population level. >>Yeah, right. You talked about all this data that's not not really used on. It's because it's not accessible. I presume it's not in in one place that somebody can analyze its not standardized. It's not normalized. Uh, is that >>right, that is the biggest. That is the biggest challenge for every healthcare provider, pair or life science organization today. If you look at this data, it's difficult to work with. Medical health. Data is really different that I siloed spread out across multiple systems, and it's sort of not incompatible formats. If you look at the last decade, I mean, one of the greatest things is we witnessed a great transformation healthcare towards digitization of the record. But your data is scattered across many of these systems anywhere from found your family history, the clinical observation, diagnosis and treatment. When you see the vast majority of that data is contained in unstructured medical records like Dr Notes P. D efs of insurance, um, of laboratory reports or insurance claims and forms with the With With Covad, we've seen in quite a bit of uptake of digital sort of, um uh, delivery of care such as telemedicine and recorded audios and videos, X rays and images, uh, the large propagation of digital health, APS and and digital assistances and on and wearables and as well as these sort of monitors like glucose, monitor or not, data come in all shapes and form and form and start across all these things. It's a huge heavy lift for any health care organization to be able to aggregate normalized stored securely on. Then also be able to kind of analyze this information and structure in a way that zizi to scale. Um uh, with regards, Thio, the kind of problems that you're going after. >>Well, Dr Cox, who We have to leave it there. Thank you so much. I have been saying for years in the Cube. When is it? That machine's gonna be able to make it make better diagnoses than doctors. Maybe that's the wrong question. Maybe it's machines helping doctors make faster and more accurate diagnoses and lowering our costs. Thanks so much for coming. >>Thank you very much. Appreciate it. Thank you. >>Thank you for watching everybody keep it right there. This is Dave Volonte. We'll be back with more coverage of aws reinvent 2020. You virtual right after this short break

>>Hey, Sue, my great to see you. Welcome to the Data Cloud Summit. Super excited to have you welcome. >>Hey, Chris. Very nice to be there. Thank you for having me >>tell us a little bit about alien spending lakhs. Tell us a little bit about yourself and your role. Italy and Benelux >>aliens, Benelux zits. Basically the aliens business in the region. Belgium, Netherlands and Luxembourg. We serve the needs of the customer here by securing the future. We actually do both PNC asses. We call it properly and casualities in life investment management and health. We do retail, uh, small and medium enterprises. I am a regional chief Data and Biggs, officer for aliens. Benelux. I report directly to the regional CEO my job here in alliance to basically drive the data and analytics agenda for aliens. Vanilla, >>cinnamon. I understand you're getting your PhD in data science. It would be great for the audience to learn a little bit more about what's driving you to do that. And kind of what? What's most interesting to you about data science? A I m l >>the reason why I started to do this because there's so much relevance. Push that which is basically driving the agenda. We need to really look at the theoretical part off it as well. To kind of concrete eyes, Andi toe bring in a certain develop dependency, consistency, timelessness, etcetera. And obviously that which we're doing is very innovative. Here, Italians, monologues driven again by relevance and which is very good for the business. But the timelessness needs to also be the sustainability the scalability needs also has to be given to this particular relevance driven topic so that we don't just create superficial impact. But we create a long lasting and everlasting impact in our competitive intelligence intelligence that building against monologues. >>That's awesome. I mean, thanks for sharing that. So So I think. Cinnamon. When when you and I met back in March 1 of the big things that you were you were considering is, you know, uh, signing up with snowflake and becoming a customer. But part of that journey was convincing Ali on spent lakhs to move to the cloud in your journey. So kind of it would be great for you to explain to the audience. You know what that journey has been like. Was it hard to convince your organization moved to the cloud, What hurdles might you have seen in your journey to the cloud? >>It was not very different to any kind of a change on the kind of effort that you need to put in a change for a normal status go set up that which exists today. So, of course, in any kind of a change, your status could change or challenge that which you bring in. There is a considerable, uh, effort that you need to put in. And it's also your responsibility to basically do that because if you don't have that energy or if you don't have that commitment and you are not able to sustain the energy of the commitment that you show in the new agenda that you bring in, then probably you're not gonna be there to see the change through. Of course, it waas difficult, obviously, because, uh, there is already existing status. Go. And there we have a lot of benefits by moving to cloud, and obviously the benefits seems very interesting. But there is skepticism, and we s alliance is from a group perspective, and Benelux perspective is full of very, very clear on a point that we cannot take advantage off the data that which we have. We want to ensure that privacy is by design. Security is by design. And we give utmost care to our customer data. Um, mhm. And all of this basically brings in tow the concept off. Okay, what is it about moving to the cloud and where are we getting exposed? Where should we basically put together? A security by design privacy with some kind of concepts before we do it and etc. Are you ready? Can be ensured that we still keep the customers data A to a place where we basically can't bust. Well, those are the things that which had to be explained. A certain level of sensitization had to be created. A certain level of awareness. Uh, then the consideration part. Yeah, all of this basically takes its own cycle. >>Awesome. Thanks for sharing that. So we're super excited to call Ali on spending lakhs of customer. Now, what are you excited about with snowflake? And I know that you're you're looking at snowflake. Is this kind of data cloud and data cloud transformation project. Tell us a little bit more about, you know, What? What excites you about Snowflake? How you think you might use stuff like, um, in this kind of transformation of Ali on spending lakhs? >>I know that snowflake is brought to us as a product by you guys, but we look at snowflake is a kind off message. We are breaking down the silos. Literally. Onda. We look at snowflake as a kind often agent to do this. Uh, this is something that which is very important to understand that whatever you do with the organizational level, you still end up with a situation where you kind of reinforce the silos. But, snowflake, we have an opportunity here to even challenge that on break the data silos. Once the data silos is broke, you basically improve the find ability of data. You basically improve the understand ability of the data accessibility of the data interpret ability on everyone sees pretty much the same truth. And that's how the silos disappear. We're very, very excited about the journey that which, which we have in front of us because we're pretty new in it. In the sense that we are going toe haven't very exciting journey as we progress, we are also looking forward to see how Snowflakes road map is going to take us to the point off arrival, as I would call it in our own data revenge in >>today we live in this kind of multi cloud, multi cloud application world. What are some of the concerns you have as you transition from, you know, having stuff in a data center to using multiple clouds to using multiple tools? You know, what's what's some of the challenges you for? See having? What are the things that you're looking for from Snowflake to help you? Um, in that journey, >>there is always a reason why we basically make a change. And the reason is always mostly towards more efficiency, effectiveness and so on and so forth, right? I mean, basically, we have Catholics challenges on this. Catholic challenges can also be addressed with this move to the cloud, except but what We should be careful and should avoid us that the cost that which we have in terms of Camp X is just does not get re attributed into another cost called articulation, cost or arbitration cost. So having a multi cloud is definitely a challenge until you have a kind off orchestrator because we are doing a business here and we don't want to care about pretty much the orchestration. The are part off it on. This needs to be taken taken into account because there is this application cloud and there is this infrastructure cloud. You can have as many clothes as you want, whatever function that which is is supporting you. But that has to be encapsulate, er abstracted away from us so that we're able to focus on the business that we're here to do. And these are certain constraints that I really had as I was thinking about multi cloud or hybrid cloud and I was even focusing on how am I going toe orchestrate all of these different things Eso that you know, you kind of feel abstracted from those things. So well, those are the constraints that I think we still have toe conquer as we progress. I think we are evolving very fastly in that area. And you are the experts in that area, and you know exactly what you're doing there. But for me, what is very important is that uh, yeah, it gets abstracted away from us, and we just get the scalability that we need the elasticity that which we need the security by design the privacy by design on. Then I think this is perfect for us. >>Awesome. So? So I think a lot of customers that are listening to this are about to jump on the same journey that you're you're embarking on. What, is there a specific use case that you decided to kind of go? You know, you know, all in on Snowflake. What was the what was the kind of the initial driver for you to say? Hey, then the business driver on you saying, Hey, I'm gonna use this use case to drive transformation within within Ali and spend lakhs, >>I think virtualization, uh, it's the keep point that comes up the top of my head the moment you speak about what even did drive me to think about snowflake as an option, right? Why virtualization? Because obviously I don't want to move huge amount of data from left, right and center, because you know that when you start optimizing such a kind of an architectural, you end up creating pockets silos, which is totally against what we want to do. We want to break silos. But in the end, just because off the infrastructure needs in the computational needs, etcetera on the response rates and stuff like that, you start to create silos, bring with virtualization and especially with the performance that with Snowflake and provide us in that area. Now it seems like a possibility that we will be able to do that. I mean, it was not something that we just thought about, let's say, a few years back, but now it's definitely possible virtualization. It's one of the key points, but when you talk in the terms of use cases, we Italians monologues do not look at use cases. Actually, we look at business initiatives, so the reason why we don't look at it as use cases is because use cases used, kind off a start and stop. But we were not in the game. Off use cases were in the game off delivering future, that which our customer really wants to be secured. That's what the business we are in and that there are no use cases. There are initiatives there that which matches to the agenda for our customer. So when you start thinking about like that one of the most important things that snowflake offices is an opportunity is to obviously create on environment, so to say, on elastic scalable, uh, situation with the computer that which we need that which basically matches one on one with the agenda for our customer. So what I mean is the data warehousing on the cloud through data warehousing on the cloud is what waas on off our driving thought processes for We did not want to go and say that we will just do, uh, do Data Lake. We will just do data hub way don't belong toe religion. So to say, we basically are very opportunistic in this approach where we say we will have a data lake. We will have a data warehouse. We will have a data hub on. We will integrate it, you know, very a semantic way that which will match to the agenda of the customer and treat the customer as a sort of centric point. >>That's great. I appreciate that. So So, um, Suderman, thank you so much for for, you know, joining us today. Um, And again, thank you for your partnership. We snowflake is super excited. I'm I'm super excited Thio participate in this journey with you. Is there anything that you kind of like to let the audience know before we wrap up? >>Very happy about the way we started Toe talk. Converse. I think the proof of value as we did was a very good engagement with you guys. I mean, you guys were really there. I really appreciate the way that you took the proof of what I've worked with many other windows in terms of proof of value. But I think you had a marked difference in the way you you brought Snowflake. Tow us. Thank you so much and keep doing the good work. >>Thanks so much cinnamon for the partnership and were super pumped on, you know, making you very successful in your project. So thank you so much. >>Thank you.

>> Announcer: From San Francisco, it's theCUBE! Covering RSA Conference 2020 San Francisco. Brought to you by SiliconANGLE Media. >> Hey welcome back, get ready, Jeff Frick here with theCUBE, we're at RSA 2020, here at Moscone, it's a really pretty day outside in San Francisco, unfortunately we're at the basement of Moscone, but that's 'cause this is the biggest thing going in security, it's probably 15,000 people, we haven't got the official number yet, but this is the place to be and security is a really really really big deal, and we're excited to have our next guest, I haven't seen her for a little while, since data privacy day. I tried to get Scott McNealy to join us, he unfortunately was predisposed and couldn't join us. Michelle Finneran Dennedy, in her new job, the CEO of DrumWave. Michelle, great to see you. >> Great to see you too, I'm sorry I missed you on privacy day. >> I know, so DrumWave, tell us all about DrumWave, last we saw you this is a new adventure since we last spoke. >> It's a new adventure, so this is my first early stage company, we're still seeking series A, we're a young company, but our mantra is we are the data value company. So they have had this very robust analytics engine that goes into the heart of data, and can track it and map it and make it beautiful, and along came McNealy, who actually sits on our board. And they said we need someone, it's all happening. So they asked Scott McNealy, who is the craziest person in privacy and data that you know and he said "Oh my God, get the Dennedy woman." So, they got the Dennedy woman and that's what I do now, so I've taken this analytics value engine, I'm pointing it to the board as I've always said, Grace Hopper said, data value and data risk has to be on the corporate balance sheet, and so that's what we're building is a data balance sheet for everyone to use, to actually value data. >> So to actually put a value on the data, so this is a really interesting topic, because people talk about the value of data, we see the value of data wrapped up, not directly, but indirectly in companies like Facebook and Google and those types of companies who clearly are leveraging data in a very different way, but it is not a line item on a balance sheet, they don't teach you that at business school next to capital assets and, right, so how are you attacking the problem, 'cause that's a huge, arguably will be the biggest asset anyone will have on their balance sheet at some point in time. >> Absolutely, and so I go back to basic principles, the same as I did when I started privacy engineering. I look and I say "Okay, if we believe the data's an asset," and I think that at least verbally, we all say the words "Yes, data is an asset," instead of some sort of exhaust, then you have to look back and say "What's an asset?" Well an asset, under the accounting rules, is anything tangible or intangible that is likely to cause economic benefit. So you break that down, what is the thing, well you got to map that thing. So where is your data? Well data tells you where it is. Instead of bringing in clip boards and saying "Hey, Jeff, my man, do you process PII?" We don't do that, we go to your system, and when you go on DrumWave, you're automatically receiving an ontology that says what is this likely to be, using some machine learning, and then every single column proclaims itself. And so we have a data provenance for every column, so you put that into an analytics engine, and suddenly you can start asking human questions of real data. >> And do you ask the questions to assess the value of the data, or is the ultimate valuation of that data in the categorization and the ontology, and knowing that I have this this this and this, or I mean we know what the real value is, the soft value is what you can do with it, but when you do the analytics on it, are you trying to get to unlock what the potential, underlying analytic value is of that data that you have in your possession? >> Yeah, so the short answer is both, and the longer answer is, so my cofounder, Andre Vellozo, believes, and I believe too, that every conversation is a transaction. So just like you look at transactions within the banking context, and you say, you have to know that it's there, creating a data ontology. You have to know what the context is, so when you upload your data, you receive a data provenance, now you can actually look at, as the data controller, you open what we call your wallet, which is your portal into our analytics engine, and you can see across the various data wranglers, so each business unit has put their data on, because the data's not leaving your place, it's either big data, small data, I don't really care data. Everything comes in through every business unit, loads up their data set, and we look across it and we say "What kind of data is there?" So there's quantitative data saying, if you took off the first 10 lines of this column in marketing, now you have a lump of data that's pure analytics. You just share those credentials and combine that dataset, you know you have a clean set of data that you can even sell, or you can create an analytic, because you don't have any PII. For most data sets, you look at relative value, so for example, one of the discussions I had with a customer today, we know when we fail in privacy, we have a privacy breach, and we pay our lawyers, and so on. Do you know what a privacy success is? >> Hopefully it's like an offensive lineman, you don't hear their name the whole game right, 'cause they don't get a holding call. >> Until they put the ball in the hole. So who's putting the ball in the hole, sales is a privacy success. You've had a conversation with someone who was the right someone in context to sign on the bottom line. You have shared information in a proportionate way. If you have the wrong data, your sale cycle is slower. So we can show, are you efficiently sharing data, how does that correlate with the results of your business unit? Marketing is another privacy success. There's always that old adage that we know that 50% of marketing is a waste, but we don't know which 50%. Well now we can look at it and say "All right," marketing can be looked at as people being prepared to buy your product, or prepared to think in a new, persuasive way. So who's clicking on that stuff, that used to be the metric, now you should tie that back to, how much are you storing for how long related to who's clicking, and tying it to other metrics. So the minute you put data into an analytics engine, it's not me that's going to tell you how you're going to do your data balance sheet, you're going to tell me how dependent you are on digital transactions versus tangible, building things, selling things, moving things, but everyone is a digital business now, and so we can put the intelligence on top of that so you, the expert in value, can look at that value and make your own conclusions. >> And really, what you're talking about then is tying it to my known processes, so you're almost kind of parsing out the role of the data in doing what I'm trying to do with my everyday business. So that's very different than looking at, say, something like, say a Facebook or an Amazon or a Google that are using the data not necessarily, I mean they are supporting the regular processes, but they're getting the valuation bump because of the potential. >> By selling it. >> Or selling it, or doing new businesses based on the data, not just the data in support of the current business. So is that part of your program as well, do you think? >> Absolutely, so we could do the same kind of ontology and value assessment for an Apple, Apple assesses value by keeping it close, and it's not like they're not exploiting data value, it's just that they're having everyone look into the closed garden, and that's very valuable. Facebook started that way with Facebook Circles way back when, and then they decided when they wanted to grow, they actually would start to share. And then it had some interesting consequences along the line. So you can actually look at both of those models as data valuation models. How much is it worth for an advertiser to get the insights about your customers, whether or not they're anonymized or not, and in certain contexts, so healthcare, you want it to be hyper-identifiable, you want it to be exactly that person. So that valuation is higher, with a higher correlation of every time that PII is associated with a treatment, to that specific person with the right name, and the same Jr. or Sr. or Mrs. or Dr., all of that correlated into one, now your value has gone up, whether you're selling that data or what you're selling is services into that data, which is that customer's needs and wants. >> And in doing this with customers, what's been the biggest surprise in terms of a value, a piece of value in the data that maybe just wasn't recognized, or kind of below the covers, or never really had the direct correlation or association that it should've had? >> Yeah, so I don't know if I'm going to directly answer it or I'm going to sidewind it, but I think my biggest surprise wasn't a surprise to me, it was a surprise to my customers. The customers thought we were going to assess their data so they could start selling it, or they could buy other data sources, combine it, enrich it, and then either sell it or get these new insights. >> Jeff: That's what they brought you in for. >> Yeah, I know, cute, right? Yeah, so I'm like "Okay." The aha moment, of course, is that first of all, the "Oh my God" moment in data rarely happens, sometimes in big research cases, you'll get an instance of some biometric that doesn't behave organically, but we're talking about human behavior here, so the "Aha, we should be selling phone data "to people with phones" should not be an aha, that's just bad marketing. So instead, the aha for me has been A, how eager and desperate people are for actually looking at this, I really thought this was going to be a much more steep hill to climb to say "Hey, data's an asset," I've been saying this for over 20 years now, and people are kind of like "Yeah, yeah, yeah." Now for the first time, I'm seeing people really want to get on board and look comprehensively, so I thought we'd be doing little skinny pilots, oh no, everyone wants to get all their data on board so they can start playing around with it. So that's been really a wake-up call for a privacy gal. >> Right, well it's kind of interesting, 'cause you're kind of at the tail end of the hype cycle on big data, with Hadoop, and all that that represented, it went up and down and nobody had-- >> Michelle: Well we thought more was more. >> We thought more was more, but we didn't have the skills to manage it, and there was a lot of issues. And so now you never hear about big data per say, but data's pervasive everywhere, data management is pervasive everywhere, and again, we see the crazy valuations based on database companies, that are clearly getting that. >> And data privacy companies, I mean look at the market in DC land, and any DCs that are looking at this, talk to mama, I know what to do. But we're seeing one feature companies blowing up in the marketplace right now, people really want to know how to handle the risk side as well as the value side. Am I doing the right thing, that's my number one thing that not CPOs are, because they all know how crazy it is out there, but it's chief financial officers are my number one customer. They want to know that they're doing the right thing, both in terms of investment, but also in terms of morality and ethics, am I doing the right thing, am I growing the right kind of business, and how much of my big data is paying me back, or going back to accountancy rules, the definition of a liability is an asset that is uncurated. So I can have a pencil factory, 'cause I sell pencils, and that's great, that's where I house my pencils, I go and I get, but if something happened and somehow the route driver disappeared, and that general manager went away, now I own a pencil factory that has holes in the roof, that has rotting merchandise, that kids can get into, and maybe the ceiling falls, there's a fire, all that is, if I'm not utilizing that asset, is a liability, and we're seeing real money coming out of the European Union, there was a hotel case where the data that they were hoarding wasn't wrong, it was about real people who had stayed at their hotels, it just was in the 90s. And so they were fined 14.5 million Euros for keeping stale data, an asset had turned into a liability, and that's why you're constantly balancing, is it value, is it risk, am I taking so much risk that I'm not compensating with value and vice versa, and I think that's the new aha moment of really looking at your data valuation. >> Yeah, and I think that was part of the big data thing too, where people finally realized it's not a liability, thinking about "I got to buy servers to store it, "and I got to buy storage, and I got to do all this stuff," and they'd just let it fall on the floor. It's not free, but it does have an asset value if you know what to do with it. So let's shift gears about privacy specifically, because obviously you are the queen of privacy. >> I like that, that's my new title. >> GDPR went down, and now we've got the California version of GDPR, love to get your update, did you happen to be here earlier for the keynotes, and there was a conversation on stage about the right to be forgotten. >> Jennifer: Oh dear god, now, tell me. >> And is it even possible, and a very esteemed group of panelists up there just talking about very simple instances where, I search on something that you did, and now I want to be forgotten. >> Did no one watch Back to the Future? Did we not watch that show? Back to the Future where all their limbs start disappearing? >> Yes, yes, it's hard to implement some of these things. >> This has been my exhaustion with the right to be forgotten since the beginning. Humanity has never desired a right to be forgotten. Now people could go from one village to the next and redo themselves, but not without the knowledge that they gained, and being who they were in the last village. >> Jeff: Speaking to people along the way. >> Right, you become a different entity along the way. So, the problem always was really, differential publicity. So, some dude doesn't pay back his debtors, he's called a bad guy, and suddenly, any time you Google him, or Bing him, Bing's still there, right? >> Jeff: I believe so. >> Okay, so you could Bing someone, I guess, and then that would be the first search term, that was the harm, was saying that your past shouldn't always come back to haunt you. And so what we try to do is use this big, soupy term that doesn't exist in philosophy, in art, the Chimea Roos had a great right to be forgotten plan. See how that went down? >> That was not very pleasant. >> No, it was not pleasant, because what happens is, you take out knowledge when you try to look backwards and say "Well, we're going to keep this piece and that," we are what we are, I'm a red hot mess, but I'm a combination of my red hot messes, and some of the things I've learned are based on that. So there's a philosophical debate, but then there's also the pragmatic one of how do you fix it, who fixes it, and who gets to decide whose right it is to be forgotten? >> And what is the goal, that's probably the most important thing, what is the goal that we're trying to achieve, what is the bad thing that we're trying to avoid, versus coming up with some grandiose idea that probably is not possible, much less practical. >> There's a suit against the Catholic Church right now, I don't know if you heard this, and they're not actually in Europe, they live in Vatican City, but there's a suit against, about the right to be forgotten, if I decide I'm no longer Catholic, I'm not doing it, Mom, I'm hearing you, then I should be able to go to the church and erase my baptismal records and all the rest. >> Jeff: Oh, I hadn't heard that one. >> I find it, first of all, as someone who is culturally Catholic, I don't know if I can be as saintly as I once was, as a young child. What happens if my husband decides to not be Catholic anymore? What happens if I'm not married anymore, but now my marriage certificate is gone from the Catholic Church? Are my children bastards now? >> Michelle's going deep. >> What the hell? Literally, what the hell? So I think it's the unintended consequence without, this goes back to our formula, is the data value of deletion proportionate to the data risk, and I would say the right to be forgotten is like this. Now having an indexability or an erasability of a one-time thing, or, I'll give you another corner case, I've done a little bit of thinking, so you probably shouldn't have asked me about this question, but, in the US, when there's a domestic abuse allegation, or someone calls 911, the police officers have to stay safe, and so typically they just take everybody down to the station, men and women. Guess who are most often the aggressors? Usually the dudes. But guess who also gets a mugshot and fingerprints taken? The victim of the domestic abuse. That is technically a public record, there's never been a trial, that person may or may not ever be charged for any offense at all, she just was there, in her own home, having the crap beat out of her. Now she turns her life around, she leaves her abusers, and it can happen to men too, but I'm being biased. And then you do a Google search, and the first thing you find is a mugshot of suspected violence. Are you going to hire that person? Probably not. >> Well, begs a whole discussion, this is the generation where everything's been documented all along the way, so whether they choose or not choose or want or don't want, and how much of it's based on surveillance cameras that you didn't even know. I thought you were going to say, and then you ask Alexa, "Can you please give me the recording "of what really went down?" Which has also been done, it has happened, it has happened, actually, which then you say "Hm, well, is having the data worth the privacy risk "to actually stop the perp from continuing the abuse?" >> Exactly, and one of my age-old mantras, there's very few things that rhyme, but this one does, but if you can't protect, do not collect. So if you're collecting all these recordings in the domestic, think about how you're going to protect. >> There's other people that should've hired you on that one. We won't go there. >> So much stuff to do. >> All right Michelle, but unfortunately we have to leave it there, but thank you for stopping by, I know it's kind of not a happy ending. But good things with DrumWave, so congratulations, we continue to watch the story evolve, and I'm sure it'll be nothing but phenomenal success. >> It's going to be a good time. >> All right, thanks a lot Michelle. She's Michelle, I'm Jeff, you're watching theCUBE, we're at RSA 2020 in San Francisco, thanks for watching, we'll see you next time. (techno music)

>> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're at Data Privacy Day at Twitter's World Headquarters in downtown San Francisco. Full-day event, a lot of seminars and sessions talking about the issue of privacy. Even though Scott McNealy in 1999 said, "Privacy's dead, get over it," everyone here would beg to differ; and it's a really important topic. We're excited to have Michelle Dennedy. She's the Chief Privacy Officer from Cisco. Welcome, Michelle. >> Indeed, thank you. And when Scott said that, I was his Chief Privacy Officer. >> Oh you were? >> I'm well acquainted with my young friend Scott's feelings on the subject. >> It's pretty interesting, 'cause that was eight years before the iPhone, so a completely different world than actually one of the prior guests we were talking about privacy is an issue in the Harvard Business Review from 125 years ago. So this is not new. >> Absolutely. >> So how have things changed? I mean that's a great perspective that you were there. What was he kind of thinking about and really what are the privacy challenges now compared to 1999? >> So different. Such a different world. I mean fascinating that when that statement was made the discussion was a press conference where we were introducing Connectivity. It was an offshoot of Java, and it basically allowed you to send from your personal computer a wireless message to your printer so that a document could come out (gasp). >> That's what it was? >> Yeah. >> Wireless printing? >> Wireless printing. And really it was gyro technology, so anything wirelessly could start talking to each other in an internet of things world. >> Right. >> So, good news bad news. The world has exploded from there, obviously; but the base premise of, can I be mobile, can I live in a world of connectivity, and still have control over my story, who I am, where I am, what I'm doing? And it was really a reframing moment of when you say privacy is dead, if what you mean by that is secrecy and hiding away and not being connected to the world around you, I may agree with you. However, privacy as a functional definition of how we define ourselves, how we live in a culture, what we can expect in terms of morality, ethics, respect, and security, alive and well, baby. Alive and well. >> (laughs) No shortage of opportunity to keep you busy. We talked to a lot of people who go to a lot of tech conferences. I have to say I don't know that we've ever talked to a Chief Privacy Officer. >> You're missing out. >> I know, so not you get to define the role, I love it. So what are your priorities as Chief Priority Officer? What are you keeping an eye on day to day as well as what are your more strategic objectives? >> It's a great question. So the rise of the Chief Privacy Officer, actually Scott was a big help in that and gave me exactly the right amount of rope to hang myself with. The way I look at it is, probably the simplest analogy is, should you have a Chief Financial Officer? >> Yeah. >> I would guess yeah, right? That didn't exist about 100 years ago. We just kind of loped along, and whoever had the biggest bag of money at the end was deemed to be successful. Where if somebody else who had no money left at the end but bought another store, you would have no way of measuring that. So the Chief Privacy Officer is that person for your digital currency. I look at the pros and the cons, the profit and the loss, of data and the data footprint for our company and for all the people to whom we sell. We think about, what are those control mechanisms for data? So think of me as your data financial officer. >> Right, right. But the data in and of itself is just stagnant, right? It's really just the data in the context of all these other applications. How it's used, where it's used, when it's used, what it's combined with, that really starts to trip into areas of value as well as potential problems. >> I feel like we scripted this before, but we didn't. >> Jeff: We did not script it, we don't script the-- >> So if I took out a rectangle out of my wallet, and it had a number on it, and it was green, what would you say that thing probably is? >> Probably Andrew Jackson on the front. >> Yeah, probably Andrew Jackson. What is that? >> A 20 dollar bill. >> Why is that a 20 dollar bill? >> Because we agree that you're going to give it to me and it has that much value, and thankfully the guy at Starbucks will give me 20 bucks worth of coffee for it. >> (laughs) Exactly. Well which could be a cup the way we're going. >> Which could be a cup. >> But that's exactly right. So is that 20 dollar bill stagnant? Yes. That 20 dollar bill just sitting on the table between us is nothing. I could burn it up, I could put it in my pocket and lose it and never see it again. I could flush it down the toilet. That's how we used to treat our data. If you recognize instead the story that we share about that piece of currency, we happen to be in a place where it's really easy to alienate that currency. I could go downstairs here and spend it. If I was in Beijing I probably would have to go and convert it into a different currency, and we'd tell a story about that conversion because our standards interface is different. Data is exactly the same way. The story that we share together today is a valuable story because we're communicating out, we're here for a purpose. >> Right. >> We're making friends. I'm liking you because you're asking me all these great questions that I would have fed you had I been able to feed you questions. >> Jeff: (laughs) But it's only that context, it's only that communicability that brings it value. We now assume as a populous that paper currency is valuable. It's just paper. It's only as good as the story that enlivens it. So now we're looking at smaller, smaller Microdata transactions of how am I tweeting out information to people who follow me? >> Jeff: Right, right. >> How do I share that with your following public, and does that give me a greater opportunity to educate people about security and privacy? Does that allow my company to sell more of my goods and services because we're building ethics and privacy into the fabric of our networks? I would say that's as valuable or more valuable than that Andrew Jackson. >> So it's interesting 'cause you talk about building privacy into the products. We often hear about building security into the products, right? Because the old way of security of building a bigger wall doesn't work any more and you really have to bake it in at all steps of the application: development, the data layer, the database, et cetera, et cetera. When you look at privacy versus security, and especially 'cause Cisco's sitting on, I mean you guys are sitting on the pipes, everything is running through your machines. >> That's right. >> How do you separate the two, how do you prioritize, and how do you make sure the privacy discussion is certainly part of that gets the right amount of relevance within the context of the security conversation? >> It's a glib answer that's much more complicated, but the security is really in many instances the what. I can really secure almost any batch of data. It can be complete gobbley gook zeroes and ones. It could be something really critical. It could be my medical records. The privacy and the data about what that context is, that's the why. I don't see them as one or the other at all. I see security and security not as not a technology but a series of verb things that you actually physically, people process technologies. That enactment should be addressed to a why. So it's kind of Peter Drucker's management of you manage what you measure. That was like incendiary advice when it first came out. Well I wanted to say that you secure what you treasure. So if you treasure a digital interaction with your employees, your customers, and your community, you should probably secure that. >> Right. But it seems like there's a little bit of a disconnect about maybe what should be treasured and what is the value with folks that have grown up. Let's pick on the young kids, not really thinking through or having the time or knowing an impact of a negative event in terms of just clicking and accepting the EULA and using that application on their phone. They just look at in a different way. Is that valid? How do they change that behavior? How do you look at this new generation, and there's this sea of data which is far larger than it used to be coming off all these devices, internet of things, obviously. People are things too. The mobile devices with all that geolocation data, and the sensor data, and then oh by the way it's all going to be in our cars and everything else shortly. How's that landscape changing and challenging you in new ways, and what are you doing about it? >> The speed and dynamics are astronomical. How do you count the stars, right? >> Jeff: (laughs) >> And should you? Isn't that kind of a waste of time? >> Jeff: Right, right. >> It used to be that knowledge, when I was a kid, was knowing what was in A to Z of the Encyclopedia Britannica. Now facts are cheap. Facts used to be expensive. You had to take time and commit to them, and physically find them, and be smart enough to read, and on, and on, and on. The dumbest kid is smarter than I was with my Encyclopedia Britannica because we have search engines. Now their commodity is how do I critically think? How do I make my brand and make my way? How do I ride and surf on a wave of untold quantities of information to create a quality brand for myself? So the young people are actually in a much better position than, I'll still count us as young. >> Jeff: Yeah, Uh huh. >> But maybe less young. >> Less young, less young than we were yesterday. >> We are digital natives, but I think I am hugely optimistic that the kids coming up are really starting to understand the power of brand: personal brand, family brand, cultural brand. And they're feeling very activist about the whole thing. >> Yeah, which is interesting 'cause that was never a factor when there was no personal brand, right? You were part of-- >> No way. >> whatever entity that you were in. >> Well, you were in a clique. >> Right. >> Right? You identified as when I was home I was the third out of four kids. I was a Roman Catholic girl in the Midwest. I was a total dork with a bowl haircut. Now kids can curate who and what and how they are over the network. Young professionals can connect with people with experience. Or they can decide, I get this all the time on Twitter actually. How did you become a Chief Privacy Officer? I'm really interested in taking a pivot in my career. And I love talking to those people 'cause they always educate me, and I hope that I give them a little bit of value too. >> Right, right. Michelle, we could go on for on and on and on. But, unfortunately, I think you got to go cover a session. So we're going to let you go. >> Thank you. >> Michelle Dennedy, thanks for taking a few minutes of your time. >> Thank you, and don't miss another Data Privacy Day. >> I will not. We'll be back next year as well. I'm Jeff Frick. You're watching theCUBE. See you next time.