to the Iran Brooks show. All right, so I think that's enough on North Korea. I want to talk about Antifa. Antifa is a so-called anti-fascist movement that has grown significantly, it's been around for quite a long time. It actually has hooks back into the 1920s and 30s in Europe. It was part of kind of the punk rock scene during the 1980s. There was then part of the anti-globalization riots and during the early 2000s. And if you remember, when they rioted in Seattle and damaged their cars there. But at least in the United States, it has grown significantly since Donald Trump was elected. There's no question if you look at traffic, if you look at membership, if you look at their activity on campuses and everywhere else, they have grown. And they've capitalized over the rise over the last couple of decades of a hard left of a, some people call it alt left, hard left, whatever you want to call it, anti-capitalist, anti-American, anti-individualistic, pro-racist, collectivist, tribalist kind of left. And a very, very, very much anti-free speech left. And they've capitalized on that. And the next step, of course, for anti-free speech left is to promote violence in the name of silencing what they call offensive speech. So you saw articles in The New York Times and elsewhere, op-eds, not articles, editorials by university professors claiming that speech is violence. And think about it, you could make that claim, right? Speech offends, that offense causes you to have, I don't know, it causes you to be depressed and that has physical consequences. And therefore, speech is violence and speech must be suppressed, just like violence is suppressed. Now, which speech, who gets to determine what's offensive, what is hate? Well, of course, the powers to be, the authorities get to decide all of that for us. But in the meantime, since the authorities are not doing that, since the authorities are not doing that, since the universities are not doing that, I mean, all these people are allowed to speak on campuses and voice their opinions. And universities are not doing much about it and the government is not doing anything about it and the police are not silencing all these people who are speaking. I mean, even neo-Nazis are speaking and demonstrating and have websites and all this stuff. Then somebody has to do something about this. This is all wrong. This is a just, this is immoral. This is evil and carnate. And therefore, what you need is Antifa to go around defending us, protecting us from speech that is violence, that is offensive, that is, the equivalent of violence. And the Antifa are always going to say, as long as they, and they have an intellectual support, they're always gonna say, look, all we're doing is self-defense. All we're doing is protecting ourselves from the things those people over there are saying, because what they're saying is so disgusting, is so offensive, it is violent. So our violence is not initiation of force. Our violence is self-defense. And you're not against self-defense. None of us are against self-defense. We're all for self-defense. We believe violence is okay in self-defense. So therefore, you cannot come after us, say Antifa, because we're just acting in self-defense and we're filling in, we're filling in for the deficiencies of the police, for the deficiencies of the legal system, for the deficiencies of our universities, for the fact that we're way too tolerant of violence from the so-called right. And speech is violence. Therefore, when they speak, we should not be tolerant of it. We should shut them down. We should silence them. So Antifa views itself as very much as a vigilante group. People out there have committed crimes. Those crimes are speech crimes. And it's the Antifa's job. It's a job that we're doing. It's Antifa's responsibility. It's Antifa's mission to bring justice to the world and to silence those who use speech in violent ways. How did I do? I mean, that was a pretty good, that was pretty good defense of Antifa, right? Yeah, and that's the problem. The problem is there's almost nobody out there who can argue against them. And that's the problem that the left faces. I think many people on the left are very uncomfortable with Antifa. And you see that in articles in the New York Times and in Atlantic Magazine and other places where they're clearly uncomfortable with us. So for example, there was an article on the rise of the violent left on the Atlantic. And it's a very good article. It's worth reading. And he documents the violence and he's a lefty. It's clear he's a lefty. But can he really argue with them? Can he really make the case of why free speech is a value? And it's less you can unless you can, unless you can argue that free, that speech is never violence unless it's incitement or fraud, right? There's specific cases which the law already recognizes where speech morphs into action, morphs into violence. But these have to be objectively defended which is not easy. So it's very difficult to argue against them now. Why is it important to argue against them? Not because you can convince any of them, but because the people are most consistent with the point of view. Ultimately shape the intellectual culture. They actually start causing people to gravitate in their direction. They actually shift the middle in their direction. They shift the entire argument in their direction. And the outcome of Antifa will be, this is my prediction, will be if not challenged. If not challenged philosophically and intellectually, put aside the police response which we'll get to. But if it's not challenged intellectually and philosophically, then their view will become legitimate. And if their view becomes legitimate, what we will get is what we already have to some extent in Europe.  And it won't be Antifa shutting down speeches. It won't be Antifa shutting down certain points of view.  But it's coming. You know it's coming. Europe has it already. And Europe usually, given the trends in the United States, Europe is where we're heading. So the First Amendment cannot stand up to a systematic, unopposed, philosophical, intellectual attack. It cannot. And who defends the First Amendment? A bunch of conservatives who often cannot make the argument for free speech. Cannot make the argument, philosophical and intellectual argument for why free speech is an absolute. For why speech is never, ever, ever violence except when it's not speech, when it is violence. Opinion cannot be violence.  It's when, you know, action is demanded. Action is the consequence. So the speech becomes action. But that is the kind of intellectual, philosophical defense that needs to be taken. You know, that's for example, what at the Anduin Institute we are doing in engaging in a philosophical, intellectual defense of free speech. Because without it, free speech will fall and Antifa will win. And that is the goal. The goal is to move, you know, in sports what they call, to move the goalposts, to move the discussion, to move the agenda. And they're winning with that because, you know, A, because they've got the media on their side and because the so-called right has almost no arguments against them. You know, so the discussion today is boiling down to Antifa versus the neo-Nazis. That's not a discussion.  Where is the intellectual right arguing against Antifa? Arguing against their points that they are making about speech, that's the essence. And that's why, you know, I'm supportive of anybody today fighting for free speech, even if I disagree with them on a lot of other things. Free speech is the issue of our time. Free speech is the issue we must protect. We must defend. We must fight for right now because it's under attack both from right and from left. And I've talked about this a lot about how Donald Trump is in attack on free speech. But the right has always been weak on free speech. The real attack is coming now from the left, which traditionally has been pro-free speech. And now it's just flipped. So now who's for free speech, really? Almost nobody, almost nobody. I, you know, just to give you an example of the right being anti-free speech. So one of the issues that has happened over the last few weeks is that some tech companies have banned, like neo-Nazis from being on their servers, or Google, of course kicked out that kid who wrote the Google memo. YouTube will not sell ads on some content and actually will ban certain people. So Patreon, so of others. And what is the right's response to that? It was not an intellectual philosophical argument about the virtue of free speech and an open discussion in society. It was, we need to regulate Google. We need to break Google up. Indeed, the left and the right have united on one agenda item, which is, let's attack Google, let's go after Google, let's break them up, let's regulate them, let's view them as a utility, let's force them to have, to accept all opinions. YouTube and everybody else. So, you know, this is a very, very scary place we find ourselves in because of, I think, the impotence of people in the right to defend free speech properly. I think they are defenders of free speech. David Rubin and a lot of the people that he has on his show, I strongly recommend the Rubin Report on YouTube. Look up, Dave Rubin on YouTube. Rubin Report on YouTube, actually, a couple of weeks ago, I was, he interviewed me, but the people he interviews are part of the people trying to articulate an intellectual philosophical defense of free speech, which is so crucial today. All right, if you want in on the conversation about Antifa, if you have any theories about Antifa, if you know what needs to be done about Antifa, or if you want to talk about free speech, generally,<PHONE_NUMBER>-888-900-3393, I'd love to hear from you. I'd love to hear what you have to say about Antifa. Have you been in any of these demonstrations? Okay, when we come back, I want to talk about what Antifa's done recently, Berkeley, Boston are the places. I want to talk about the media's response to Antifa, which I think is interesting. And I want to talk about the ever-growing definition of fascism that Antifa relies on in order to sustain itself. All right, so if you have anything to say about any of that,<PHONE_NUMBER>, you're listening to your own book show on the Blaze Radio Network, we're here every Sunday from 11 and one Pacific time. And... 10. You know, we'll talk to you right after this break that's coming up. Five. Five. The Iraq Book Show. All right, so maybe the most important topic of our generation, of our time, will be free speech, defending free speech, arguing for free speech, and crushing the arguments made by these lefties and by the right on this issue of free speech. You have to change the way people think about this issue. We have to. We have to insist. Now, I'm not going to give you the whole philosophical argument here. I recommend, I have a number of podcasts on this issue. You can look at them on the podcast app. You can also go to YouTube and look up your on-book free speech. You'll find a lot of videos that I've done, talks that I've done. I'm going to be giving some talks in Europe this next month on free speech. Those will be up on YouTube. And I also want to recommend Steve Simpson from the Ironman Institute's book, Defending Free Speech. You can get it on Amazon. It's like $6.95 on a kindola paperback. It's definitely worth getting with essays about free speech. And there's a lot more to come. Look up on the Ironman Institute website. We have a lot of information about free speech. But the essential argument is this, in my view. And this is why it's hard because some of the preconditions for this argument don't exist in our culture. Our culture, we have to understand that human survival, human flourishing depends on the free exercise of the human mind. Reason is man's basic means of survival. It is by means by which we survive and thrive and flourish on this earth. It's by use of our mind. It's by use of our reason. It's our thinking capabilities, right? I hope that's obvious. It isn't. I know it isn't. To most people, it isn't. To 90% of people, maybe it isn't. Now, what is the product of thinking? The product of thinking is some kind of action. And one of those actions, one of the most important actions is speaking, writing, conveying the content of your thought. It's letting the world know. And if you have, if thinking is so important, we must protect it. And then we must protect the products of that thought. The products of the thought must be protected because otherwise people won't do the thinking. They won't do the thinking if you can't write. You know, it's not a surprise that there are more scientists once science is freed up from religious authoritarianism than there was during the period where the Catholic church controlled everything. And if you were a scientist and discovered something new, there was the threat of being burned to the stake.  So you have to respect thinking and you have to respect the product of thinking. And you know, one product, the most important product of thinking is speech. It's the ability to convey that thinking to other people, to teach, to educate. And some of the thinking is really, really bad.    The government, people with guns, we know how that ends. You have to allow for the junk, for the garbage, for the offensive, for the stupid, in order to get to the truth, in order to get to the truth. And some of us will never know what is true, what is not when somebody says it today, because it's not our field, it's not our profession.  We just don't know. So who gets a judge? Well, in the end of the day, the market does.   If I don't like what you're saying, if I think it's untrue, I think it's false, I shouldn't have the ability to silence you. And if we do, then the future is over. Then we slowly decline into authoritarianism, into the rule by those who get to decide what is true and what is not, what is allowed and what is not, what can be spoken and what cannot, what can be thought and what cannot. But that's the world Antifa wants to take us in. And it is, they're out there protecting, protecting, what they view as, right? You know, protecting us from fascists. But this is the problem Antifa faces. Well, it doesn't really, it's not a real problem. Problem Antifa has is, they're not that many neo-Nazis and they're not that many white supremacists, they're not that many fascists, explicit fascists in America today. Not real fascists, fascists who believe in authoritarian government and the silencing of speech and the police states and, you know, in control over the entire economy. They're not that many real fascists. They're quite, they're too many for my liking and they're more than probably most people think, but they're not that many. But Antifa doesn't view those people as fascists. Antifa is not interested in a dictionary definition of fascism. Antifa's not interested in an historical definition of fascism. Antifa's not interested in knowledge. They're interested in emotion. And to them, a fascist is anybody they disagree with. Anybody that is outside of the leftist norm, anybody outside of what they've been taught is acceptable. Anything outside of convention, leftist academic convention. So, and you know, there was a good article, I don't agree with all of it, but there were pieces of it. Holman Jenkins wrote a good article about this if a couple of, I guess about a week ago, a week and a half ago. The article is called The Great Nazi Scare of 2017. The Great Nazi Scare of 2017. Now, I don't agree with some of what he writes, but a lot of what he writes is interesting. He's one of my favorite authors generally. He writes with a Wall Street Journal two, three times a week.    So anything, any position you take, which is not leftist, which is not borderline socialist, which is not, you know, on somewhere on the left spectrum of economic issues, let's say, because the right left spectrum is useless when it comes to a lot of these issues.  And, you know, so if you're tough on foreign policy, this is another one. If you say the kind of things I said earlier in the show about North Korea, you're obviously a racist and a fascist.  Now, I know this because I've been a target of this, right?  What's that? To give a talk on free speech.  And my event, they try to shut it down.  Why? Because I hold views that are not part of this leftist, you know, mainstream. And Antifa is there to protect the conventional leftist view. All right, when we come back, we'll kind of wrap up the show. But before we do that, we have to take this break. You're listening to your own book show on the Blaze Radio Network. So, we're talking about Antifa. And Antifa's not interested in going after fascists, real fascists. Antifa's interested in going after anybody who disagrees with them. Antifa's interested in violence, and you could see that in Boston. I know a few soap pictures of the demonstration in Boston. Anybody who was, I don't know, a Trump supporter or anybody who argued with them got beaten up. And when they ran out of people to beat up, they started throwing rocks and bottles full of urine at the police. So, Antifa's not interested in real fascists. That is not what they were about. They were interested in violence. They're interested in destruction. And they target, at the end of the day, is the police. That's what they really hate. Because it's not that Antifa are communists. People love to throw out communists and neo-Moxism and stuff like that. But these people are much worse than communists. They're much worse than Marxists because they don't believe in anything. They're nihilists. They are nihilists. They're anarchists. They want to destroy for the sake of destroying.   A communist is about as corrupt intellectually as you can get, an ideology that's responsible for the death of over 100 million people.  They want to get all everything. They have no ideology, no vision. They are militant. They're violent. They want to destroy. They want to knock down. They want to break stuff. That's all they care about. And they can't be reasoned with. They can't be, you can't discuss anything with them. Right? In Berkeley, again, they were just beating people up. Again, if you expressed an opposing position.  You might disagree with him. I disagree with him on a lot of things. But he's not a fascist. So, Antifa is not about fascism. Antifa is about using violence to silence and ultimately control all those who you disagree with. And it's not for anything. They're not for an agenda. At least with the communists, you'd say, look, communist, it's a bad system. It doesn't work. These guys don't want a system. They just want the entire focus. Everything about them is driven by hate and destruction. It's not geared towards establishing a dictatorship like in North Korea. I mean, that is the outcome, but it's not what they dream about. They don't dream about some utopia which the proletarian all commune spiritually and work hard to enhance human life, which is kind of the ridiculous notion of a communist utopia. No, they don't care about any of that. Indeed, I wouldn't be surprised if these guys would start killing commies if communism was a thing. Communism is not a thing. What's a thing is nihilism. That's the thing. It's just a pure joy and destroying stuff.  And that darkness in their soul is an anti-value darkness, an anti-value orientation. That's at the end what they are.  It's not. They are morally culpable, are morally responsible. But some of them might grow out of it, but these are bad people. These are bad people. And they need to be pointed out. And one of the great evils of the world in which we live today is that the media is culpable here because the media says nothing about them. They don't talk about them. You know, again, once in a while you'll get a good article like in Atlantic about the rise of the violence left. Now it's true, as the New York Times keep pointing out, they haven't killed that many people. Two minutes. They've only killed some. Some is enough.  It's just a matter of time.  And they will silence more. So the media here is culpable by not reporting. How much did you see about Boston and about Berkeley? Some. But with no judgment. Imagine if those were racist doing the same kind of damage. The media would have been all over the story and they would have been condemning it left and right. But when it's Antifa, nobody says a word. When it's the left, nobody says a word. And partially because. Certainly the left, but even the right today have no philosophical, intellectual arguments about the fundamental issue that Antifa is bringing out. How do you address speech when it is offensive? So at the end of the day, at the end of the day, I still believe that this is a philosophical battle. This is an intellectual battle. Yeah, I mean, it would be nice that the police actually protected us and they better start doing that. But we will now win. We cannot win unless we launch a free speech offensive. A philosophical offensive. 30. An intellectual offensive. And one grounded on the value of reason, on the virtue of rationality. Any defense short of that will fail and the Antifas of the world will win. All right, we will win though. We're gonna launch that offensive. You're listening to your own book show. We're here on the Blaze Radio Network every Sunday from 11 to one, 11 to one Pacific time. And thanks for listening. Three. Clear. Applying the principles of... All right. Thanks, Ellie. Thank you. I'll see you next week. I will actually next week. So just...


From around the globe, it's theCUBE with digital coverage of Enterprise Data Automation and event series brought to you by Io Tahoe. Hi, everybody, we're back. We're talking about Enterprise Data Automation. The hashtag is data automated and we're going to really dig into data migrations. Data migrations are risky, they're time consuming and they're expensive. Youssef Khan is here. He's the head of partnerships and alliances at Io Tahoe coming again from London. Hey, good to see you, Youssef. Thanks very much. Thank you, Dave. Great time. So your role is interesting. We're talking about data migrations. You're going to head of partnerships. What is your role specifically and how is it relevant to what we're going to talk about today? Well, I work with the various businesses such as cloud companies, systems integrators, companies that sell operating systems, middleware, all of whom are often quite well embedded within company IT infrastructures and have existing relationships. Because what we do fundamentally makes migrating to the cloud easier and data migration easier, there are lots of businesses that are interested in partnering with us and we're interested in partnering with. So let's set up the problem a little bit and then I want to get into some of the data. As I said, migrations are risky, time consuming, expensive, they're oftentimes a blocker for organizations to really get value out of data. Why is that? I think, I mean, all migrations have to start with knowing the facts about your data. And you can try and do this manually, but when you have an organization that may have been going for decades or longer, they will probably have a pretty large legacy data estate. So they'll have everything from on-premise mainframes, they may have stuff which is partly in the cloud, but they probably have hundreds, if not thousands of applications and potentially hundreds of different data stores. Now, their understanding of what they have is often quite limited because you can try and draw manual maps, but they're out of date very quickly every time the data changes, the manual map set of date and people obviously leave organizations over time. So the kind of tribal knowledge that gets built up is limited as well. So you can try and map all that manually. You might need a DBA, database analyst or a business analyst, and they might go in and explore the data for you, but doing that manually is very, very time consuming. This can take teams of people months and months, or you can use automation just like Webster Bank did with Iotaho and they managed to do this with a relatively small team in a timeframe of days. Yeah, we talked to Paula from Webster Bank, awesome discussion. So I wanna dig into this migration and let's pull up a graphic. It'll talk about, we'll talk about what a typical migration project looks like. So what you see here is, it's very detailed, I know, it's a bit of an eye test, but let me call your attention to some of the key aspects of this and then Yusef, I want you to chime in. So at the top here, you see that area graph, that's operational risk for a typical migration project and you can see the timeline and the milestones. That blue bar is the time to test, so you can see the second step data analysis. It's talking 24 weeks, so very time consuming and then let's not get, dig into the stuff in the middle, the fine print, but there's some real good detail there, but go down the bottom, that's labor intensity in the bottom and you can see high is that sort of brown and you can see a number of data analysis, data staging, data prep, the trial, the implementation, post-implementation fixtures the transition to BAU which I think is business as usual. Those are all very labor intensive. So what are your takeaways from this typical migration project? What do we need to know, Yusef? I mean, I think the key thing there is when you don't understand your data upfront, it's very difficult to scope and to set up a project because you go to business stakeholders and decision makers and you say, okay, we wanna migrate these data stores, we wanna put them in the cloud most often, but actually you probably don't know how much data is there. You don't necessarily know how many applications it relates to. You don't know the relationships between the data. You don't know the flow of the data, so the direction in which the data is going between different data stores and tables. So you start from a position where you have pretty high risk and to probably alleviate that risk, you probably stack your project team of lots and lots of people to do the next phase, which is analysis. And so you've set up a project which has got a pretty high cost. The bigger the project, the more people, the heavier the governance, obviously. And then they're then in the phase where they're trying to do lots and lots of manual analysis. Manual analysis, as we all know, and the idea of trying to relate data that's in different data stores relating individual tables and columns for a very time-consuming, expensive. If you're hiring in resource from consultants or systems integrators externally, you might need to buy or to use third-party tools. As I said earlier, the people who understand some of those systems may have left a while ago. So you're in a high-risk, high-cost situation from the off, and the same thing sort of develops through the project. What you find with IOTAHO is that we're able to automate a lot of this process from the very beginning because we can do the initial data discovery run, for example, automatically. So you very quickly have an automated view of the data, a data map, and the data flow that's been generated automatically. Much less time and effort and much less cost ultimately. Okay, so I want to bring back that first chart and I want to call your attention to, again, that area graph, the blue bars, and then down below that labor intensity. And now let's bring up the same chart but with a sort of an automation injection in here. And now, so you now see the sort of, it's called, so it's celebrated by IOTAHO. Okay, great, and we're going to talk about this, but look what happens to the operational risk, a dramatic reduction in that graph. And then look at the bars, the bars, those blue bars, data analysis went from 24 weeks down to four weeks. And then look at the labor intensity. It was all these were high, data analysis, data staging, data prep, trial, post-implementation fixtures and transition to BAU. All of those went from high labor intensity, so we've now attacked that and gone to low labor intensity. Explain how that magic happened. Let's take the example of a data catalog.  Imagine trying to do that manually. You need to go into every individual data store. You need a DBA and a business analyst for each data store. They'd need to do an extract of the data, they'd need to do the tables individually. They'd need to cross-reference that with other data stores and schemas and tables. You've probably done that with a mother of all Excel spreadsheets. And it would be a very, very difficult exercise to do. I mean, in fact, one of our reflections as we automate lots of these things is, it accelerates the ability to automate, but in some cases, it also makes it possible for enterprise customers with legacy systems, like tech banks, for example, they quite often end up staying on mainframe systems that they've had in place for decades and not migrating away from them because they're not able to actually do the work of understanding the data, de-duplicating the data, deleting data that isn't relevant, and then confidently going forward to migrate. So they stay where they are with all the attendant problems of systems that are out of birth support. Go back to the data catalog example. Whatever you discover in data discovery has to persist in a tool like a data catalog. And so we automate data catalogs, including our own. We can also feed others, but we have our own. The only alternative to this kind of automation is to build out this very large project team of business analysts, of DBAs, project managers, process analysts, to gather all the data, to understand that the process of gathering the data is correct, to put in the repository, to validate it, et cetera, et cetera. We've gone into organizations and we've seen them ramp up teams of 20, 30 people, costs of two, three, four million pounds a year and a timeframe of 15 to 20 years just to try and get a data catalog done. And that's something that we can typically do in a timeframe of months, if not weeks. And the difference is using automation. And if you do what I've just described in this manual situation, you make migrations to the cloud prohibitively expensive. Whatever saving you might make from shutting down your legacy data stores will get eaten up by the cost of doing it unless you go with a more automated approach. Okay, so the automated approach reduces risk because you're not going to stay on project plan, ideally.  And then that data catalog, people are afraid that their family jewels data is not going to make it through to the other side. So that's something that you're addressing. And then you're also not boiling the ocean. You're really taking the pieces that are critical and the stuff that you don't need, you don't have to pay for as part of this process. It's a very good point. I mean, one of the other things that we do and we have specific features to do is to automatically analyze data for duplication at a row level or a record level and redundancy at a column level. So as you say, before you go into a migration process, you can then understand actually, this stuff here is duplicative. We don't need it. Quite often, if you put data in the cloud, you're paying obviously for storage space or for compute time. The more data you have in there that's duplicated, that's pure cost you should take out before you migrate. Again, if you're trying to do that process of understanding what's duplicated manually off tens or hundreds of days of stores, it will take you months if not years. You use machine learning to do it in an automatic way and it's much, much quicker. I mean, there's nothing I'd say about the net cost and benefit of IOTAHO. Every organization we work with has a lot of money existing sunk costs in their IT. So they'll have ERP systems like Oracle or Data Lakes which they've spent good time and money investing in. But what we do by enabling them to transition everything to their strategic future repositories is accelerate the value of that investment and the time to value that investment. So we're trying to help people get a value out of their existing investments and data estate, close down the things that they don't need and enable them to go to a kind of brighter and more efficient future. Well, and I think as well, you know, once you're able to, and this is a journey, we know that, but once you're able to go live and you're infusing sort of a data mindset, a data-oriented culture, I know it's somewhat buzzwordy but when you see it in organizations, you know it's real and what happens is you've dramatically reduced that end cycle time of going from data to actually insights. Data is plentiful, but insights aren't and that is what's going to drive competitive advantage over the next decade and beyond. Yeah, definitely and you can only really do that if you get your data estate cleaned up in the first place. I've worked with and managed teams of data scientists, big data engineers, business analysts, people who are pushing out dashboards and are trying to build machine learning applications. You'll know, you know, the biggest frustration for lots of them and the thing that they spend far too much time doing is trying to work out what the right data is and cleaning data, which really you don't want a highly paid data scientist doing with their time. But if you sort out your data estate in the first place, get rid of deduplication, perhaps migrate to a cloud store where things are more readily accessible and it's easy to build connections and to use native machine learning tools, you're well on the way up the data maturity curve and you can start to use some of those more advanced applications. Youssef, what are some of the prerequisites, maybe the top few or two or three that I need to understand as a customer to really be successful here? I mean, is it skill sets? Is it mindset, leadership buy-in? What do I absolutely need to have to make this successful? Well, I think leadership is obviously key. Being able to sort of set the vision for people will always be key. One of the great things about IOTAHO though is you can use your existing staff to do this work if you use our automation platform. There's no need to hire expensive people. IOTAHO is a no-code solution. It works out of the box. You just connect to the source and then your existing staff can use it. It's very intuitive. It has easy to use user interface. There's no need to invest vast amounts with large consultancy if you may well charge in the earth. And you are actually at a bit of an advantage if you've got existing staff who are close to the data who are subject matter experts or can use it because they can very easily learn how to use the tool and then they can go in and they can write their own data quality rules and they can really make a contribution from day one. When we go into organizations and we connect one of the great things about the whole experience of IOTAHO is we can get tangible results back within the day. Usually within an hour or two we're able to say, okay, we've started to map the relationships here. Here's a data map of the data that we've analyzed. Here are some thoughts on what your sensitive data is because it's automated because it's running algorithms across data. And that's what people really should expect. And you know this because you're dealing with the ecosystem. We're entering a new era of data and many organizations to your point they just don't have the resources to do what Google and Amazon and Facebook and Microsoft did over the past decade to become data dominant, trillion dollar market cap companies. Incumbents need to rely on technology companies to bring that automation, that machine intelligence to them so they can apply it. They don't want to be AI inventors. They want to apply it to their businesses. So, and that's what really was so difficult in the early days of so-called big data. You had this too much complexity out there. And now companies like IOTAHO are bringing tooling and platforms that are allowing companies to really become data-driven. Your final thoughts, please, Yusef. That's a great point, David. And in a way, it brings us back to where we began in terms of partnerships and alliances that completely agree. We're at a really exciting point where we can take applications like IOTAHO we can go into enterprises and help them really leverage the value of these type of machine learning algorithms and AI. We work with all the major cloud providers, AWS, Microsoft Azure, Google Cloud Platform, IBM, Red Hat, and others. And we really, I think for us, the key thing is that we want to be the best in the world at enterprise data automation. We don't aspire to be a cloud provider or even a workflow provider. But what we want to do is really help customers with their data, without automated data functionality, in partnership with some of those other businesses so we can leverage the great work they've done in the cloud, the great work they've done on workflows, on virtual systems, and in other areas. And we help customers leverage those investments as well. But our heart, we've really targeted at just being the best enterprise data automation business in the world. Massive opportunities not only for technology companies, but for those organizations that can apply technology for business advantage. Yousef Khan, thanks so much for coming on theCUBE. Thank you very much, I appreciate it. All right, and thank you for watching everybody. We'll be right back right after this short break.