from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante snowflake they love the stock at 400 and hated at 165 that's the nature of the business i guess especially in this crazy cycle over the last two years of lockdowns free money exploding demand and now rising inflation and rates but with the fed providing some clarity on its actions the time has come to really dig into the fundamentals of companies and there's no tech company that's more fun to analyze than snowflake hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we look at the action of snowflake stock since its ipo why it's behaved the way it has how some sharp traders are looking at the stock and most importantly what customer demand looks like the stock has really provided some great theater since its ipo i know people who got in at 120 before the open and i know lots of people who kind of held their noses and bought the stock on day one at over 300 a day when it closed at around 240 that first day of trading snowflake hit 164 this week it's all-time low as a public company as my college roommate chip simonton a long time trader told me when great companies trade at all times time lows because of panic it's worth taking a shot he did now of course the stock could go lower there's geopolitical risk and the stock with a 64 billion market cap is expensive for a company that's forecast to do around 2 billion in product revenue this year and remember i don't recommend stocks you shouldn't take my advice and my comments you got to do your own research but i have lots of data and i have opinions and i'm willing to share that with you stocks like snowflake crowdstrike z-scaler octa and companies like this are highly volatile when markets are moving up they're going to move up faster than the mean when they're declining they're going to drop more severely and that's clearly what's happened to snowflake so with a company like this you when you see panic selling you'll also see panic buying sometimes like we we've seen with this name it went from 220 to 320 in a very short period earlier snowflake put in a short-term bottom this week and many traders feel the issue was oversold so they bought okay but not everyone felt this way and you can see this in the headlines snowflake hits low but cloud stocks rise and we're going to come back to that is it a buy don't buy the dip buy the dip and what snowflake investors can learn from microsoft and from the street.com snow stock is sliding on the back of ill-conceived guidance and to that i would say that conservative guidance these days is anything but ill-conceived now let's unpack all this a bit and to do so i reached out to ivana delevska who has been on this program before she's with spear invest a female-led etf that goes deep into understanding supply chains she came on breaking analysis and laid out her thesis to buy the dip on snowflake this is a while ago she told me currently spear still likes snowflake and has doubled its position let me share her analysis she called out two drivers for the downside interest rates you know rising of course in snowflakes guidance which my own publication called weak in that previous chart that i just showed you so let's dig into that a bit snowflake guided for product revenues of 67 year on year which was below buy side expectations but i believe within sell side consensus regardless the guide was nuanced and driven by snowflake's decision to pass along price efficiencies to customers from optimizing processor price performance predominantly from aws's graviton too this is going to hit snowflakes revenue a net of about a hundred million dollars this year but the timing's not precise because it's going to hit 165 million but they're going to make up 65 million in increased demand frank slootman on the earnings call made this very clear he said quote this is not philanthropy this stimulates demand classic slootman the point is spear and other bulls believe that this will result in a gain for snowflake over the medium term and we would agree price goes down roi gets better you throw more projects at snowflakes customers going to buy more snowflake and when that happens and it gives the company an advantage as they continue to build their moat it's a longer term bet on cloud and data which are good bets now some of this could also be competitive pressures there have been you know studies that are out there from competitors attacking snowflakes pricing and price performance and they make comparisons oracle's been pretty aggressive as have others but so far the company's customers continue to consume now at a very fast rate now on on this front what can we learn from microsoft that applies to snowflake that's the headline here from benzinga so the article quoted a wealth manager named josh brown talking about what happened to microsoft after the dot-com bubble burst and how they quadrupled earnings over the next decade and the stock went sideways suggesting the same thing could happen to snowflake now i'd like to make a couple of comments here first at the time microsoft was a 23 billion dollar company and it had a monopoly and was already highly profitable steve ballmer became the ceo of microsoft right after the dot-com bubble burst and he hugged onto windows for dear life and lived off of microsoft's pc software monopoly microsoft became an extremely profitable and remarkably uninteresting caretaker of a pc in on-prem software estate during balmer's tenure so i just don't see the comparison as relevant snowflake you know they're going to make struggle for other reasons but that one didn't really resonate with me what's interesting is this chart it poses the question do cloud and data markets behave differently it's a chart that shows aws growth rates over time and superimposes the revenue in the red in q1 2018 aws generated 5.4 billion dollars in revenue and that was growing at the time at nearly a 50 rate now that rate as you can see decelerated quite significantly as aws grew to a 50 billion dollar run rate company that down below where you see it bottoms now it makes sense right law of large numbers you can't keep growing that fast when you get that big well oops look what happened in 2021 aws's growth rate bottoms in the high 20s and then rockets back up to 40 this past quarter as aws surpasses a 70 billion dollar run rate so you have to ask is cloud different is data different is cloud data different or data cloud different let's put it in the snowflake parlance can cloud because of its consumption model and the speed of innovation and ecosystem depth and breadth enable snowflake to exhibit lots of variability in its growth rates versus a say progressive and somewhat linear decline as the company grows revenue which is what you would expect historically and part of the answer relates to its market size here's a chart we've shared before with some additions it's our version of snowflake's total available market they're tam which snowflake's version that that blue data cloud thing superimposed on the right it shows the various layers of market opportunity that we came up with that that snowflake and others we think have in front of them emerging from the disruption of legacy data lakes and data warehouses to what snowflake refers to as its data cloud we think about the data mesh concept and decentralized data architectures with domain ownership and data product and service builders as consistent with snowflake's data cloud vision where snowflake data stores are nodes they're just simply discoverable nodes on the mesh you could have you know data bricks data lakes you know s3 buckets on that mesh it doesn't matter they can be discovered they can be shared and of course they're governed in a federated model now in snowflake's model it's all inside the snowflake data cloud that's fine then you'll go to the out years it gets a little fuzzy you know from edge locations and ai inference it becomes massive and decision making occurs in real time where machines and machine data take over the world instead of you know clicks and keystrokes sounds out there but it's real and how exactly snowflake plays there at this point is unclear but one thing's for sure there'll be a lot of data and it's going to find its way into snowflake you know snowflake's not a real-time engine it's an analytical system it's moving into the realm of data science and you know we've talked about the need for you know semantic layer between those those two worlds of analytics and data science but expanding the scope further out we think that snowflake is a big role to play in this future and the future is massive okay check you got the big tam now as someone that looks at companies through a fundamentals prism you've got to look obviously at the markets in the tan which we just did but you also want to understand customers and it's not hard to find snowflake customers capital one disney micron alliance sainsbury sonos and hundreds of other companies i've talked to snowflake customers who have also been customers of oracle teradata ibm neteza vertica serious database practitioners and they tell me it's consistent soulflake is different they say it's simpler it's more agile it's less complicated to secure and it's disruptive to their traditional ways of doing data management now of course there are naysayers i've spoken to a number of analysts that feel snowflake is deficient in areas like workload management and course complex joins and it's too specialized in a world where we're seeing the convergence of analytics and transactional workloads our own david floyer believes that what oracle is doing with mysql heatwave is radically disruptive to many of the database architectures and blows away anything out there and he believes that snowflake and the likes of aws are going to have to respond now this the other criticism here is that snowflake is not architected for real-time inference where a lot of that edge activity is is going to happen it's a multi-hundred billion dollar market and so look snowflake has a ton of competition that's the other thing all the major cloud players have very capable and competitive database platforms even though they all partner with snowflake except oracle of course but companies like databricks and have garnered tons of vc other vc funded companies have raised billions of dollars to do this kind of elastic consumption based separate compute from storage stuff so you have to always keep an open mind and be aware of potential blind spots for these companies but to the criticisms i would say look snowflake they got there first and watch their ecosystem it's a real key to its continued success snowflake's not going to go it alone and it's going to use its ecosystem partners to expand its reach and accelerate the network effects and fill those gaps and it will acquire its stock is valuable so it should be doing that just as it did with streamlit a zero revenue company that it bought for 800 million dollars in stock and cash just recently streamlit is an open source python library that gets snowflake further deeper into that data science space that data brick space and look watch what snowflake is doing with snowpark it's an api library for processing data and building data intensive applications we've talked about snowflake essentially being becoming the super cloud and building this sort of path-like layer across clouds rather than trying to do it all themselves it seems snowflake is really staring at the api economy and building its ecosystem to plug those holes so let's come back to the customers here's a chart that shows snowflakes customer spending momentum or net score on the the top line that's the vertical axis and pervasiveness in the data or market share and that bottom brown line snowflake has unprecedented net scores and held them up for many many quarters as you can see here going back you know a couple years all leading to its expanded market penetration and measured as pervasiveness of so-called market share within the etr survey it's not like idc market share it's pervasiveness in the data set now i'll say this i don't see how this is sustainable i've been waiting for this to moderate i wouldn't be surprised to see snowflake come back to earth a little bit i think they'll clearly still be highly elevated based on the data that i've seen but but i could see in in one or more of the etr surveys this year this starting to moderate as they get they get big it's just it has to happen um but i would again expect them to have a high spending velocity score but i think we're going to see snowflake you know maybe porpoise a bit here meaning you know it moderates it comes back up it's just really hard to sustain this piece of momentum and higher train retain and scale without absorbing some some friction and some head woods that's going to slow you down but back to the aws growth example it's entirely possible that we could see a similar dynamic with snowflake that you saw with aws and you kind of see it with salesforce and servicenow very successful large entrenched entrenched companies and it's very possible that snowflake could pull back moderate and then accelerate that growth even though people are concerned about the moderated guidance of 80 percent growth yeah that's that's the new definition of tepid i guess i look i like to look at other some other metrics the one that really called you know my my my attention was the remaining performance obligations this last quarter rpo snowflakes is up to something like 2.6 billion and that is a forward-looking indicator of of future revenues so i want to i'd like to see that growing and it's growing at a fast pace so you're going to see some ups and downs with snowflake i have no doubt but i think things are still looking pretty solid for the company growth companies like snowflake and octa and z scalar those other ones that i mentioned earlier have probably been repriced and refactored by investors while there's always going to be market and of course geopolitical risk especially in these times fundamentals matter you've got huge market well capitalized you got a leadership position great products and strong customer adoption you also have a great team team is something else that we look for we haven't touched on that but i'll leave you with this thought everyone knows about frank slootman mike scarpelli and what they've accomplished in their years of working together that's why the stock you know in ipo was was so overvalued they had seen these guys do it before slootman just documented in all this in his book amp it up which gives great insight into the history of of that though you know that pair and and the teams that they've built the companies that they've built how he thinks about building companies and markets and and how you know total available markets super important but the whole philosophy and culture that that he's building in his management style but you got to wonder right how long is this guy going to keep going what keeps him motivated you know i asked him that one time here's what he said why i mean are you in this for the sport what's the story here uh actually that that's not a bad way of characterizing it i think i am in it uh you know for the sport uh you know the only way to become the best version of yourself is to be uh to be under the gun and uh you know every single day and that's that's certainly uh what we are it sort of has its own rewards building great products building great companies uh you know regardless of you know uh what the spoils may be uh it has its own rewards and i i it's hard for people like us to get off the field and uh you know hang it up so here we are so there you have it he's in it for the sport how great is that he loves building companies and that my opinion that's how frank slootman thinks about success it's not about money money's the byproduct of success as earl nightingale would say success is the progressive realization of a worthy ideal i love that quote building great companies building products that change the world changing people's lives with data and insights creating jobs creating life-altering wealth opportunities not for himself but for thousands of employees and partners i'd say that's a pretty worthy ideal and i hope frank slootman sticks with it for a while okay that's it for today thanks to stephanie chan for the background research she does for breaking analysis alex meyerson on production kristen martin and cheryl knight on social with rob hoff on siliconangle and thanks to ivana delevska of spear invest and my friend chip symington for the angles from the money side of things remember all these episodes are available as podcasts just search breaking analysis podcast i publish weekly on wikibon.com and siliconangle.com and don't forget to check out etr.plus for all the survey data you can reach me at devolante or david.velante siliconangle.com and this is dave vellante for cube insights powered by etrbsafe stay well and we'll see you next time [Music] you

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante last week's aws re invent brought into focus the degree to which cloud computing generally and aws specifically have impacted the technology landscape from making infrastructure orders of magnitude simpler to deploy to accelerating the pace of innovation to the formation of the world's most active and vibrant infrastructure ecosystem it's clear that aws has been the number one force for change in the technology industry in the last decade now going forward we see three high-level contributors from aws that will drive the next 10 years of innovation including one the degree to which data will play a defining role in determining winners and losers two the knowledge assimilation effect of aws's cultural processes such as two pizza teams customer obsession and working backwards and three the rise of super clouds that is clouds that run on top of hyperscale infrastructure that focus not only on i.t transformation but deeper business integration and digital transformation of entire industries hello everyone and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll review some of the takeaways from the 10th annual aws re invent conference and focus on how we see the rise of super clouds impacting the future of virtually all industries one of the most poignant moments for me was a conversation with steve mullaney at aw aws re invent he's the ceo of networking company aviatrix now just before we went on the cube nick sterile one of aviatrix's vcs looked up at steve and said it's happening now before i explain what that means this was the most important hybrid event of the year you know no one really knew what the crowd would be like but well over twenty 000 people came to reinvent and i'd say at least 25 to 26 000 people attended the expo and probably another 10 000 or more came without badges to have meetings and side meetings and do networking off the expo floor so let's call it somewhere between thirty to forty thousand people physically attended the reinvent and another two hundred thousand or more online so huge event now what nick sterile meant by its happening was the next era of cloud innovation is upon us and it's happening in earnest the cloud is expanding out to the edge aws is bringing its operating model its apis its primitives and services to more and more locations yes data and machine learning are critical we talk about that all the time but the ecosystem flywheel was so evident at this year's re invent more so than any other re invent partners were charged up you know there wasn't nearly as much chatter about aws competing with them rather there was much more excitement around the value that partners are creating on top of aws's massive platform now despite aggressive marketing from competitive hyperscalers other cloud providers and as a service or on-prem slash hybrid offerings aws lead appears to be accelerating a notable example is aws's efforts around custom silicon far more companies especially isvs are tapping into aws's silicon advancements we saw the announcement of graviton 3 and new chips for training and inference and as we've reported extensively aws is now on a curve a silicon curve that will outpace x86 vis-a-vis performance price performance cost power consumption and speed of innovation and its nitro platform is giving aws and its partners the greatest degree of optionality in the industry from cpus gpus intel amd and nvidia and very importantly arm-based custom silicon springing from aws's acquisition of annapurna aws started its custom silicon journey in 2008 and is and it has invested massive resources into this effort other hyperscalers notably microsoft google and alibaba which have the scale economics to justify such custom silicon efforts are just recently announcing initiatives in this regard others who don't have the scale will be relying on third-party silicon providers a perfectly reasonable strategy but because aws has control of the entire stack we believe it has a strategic advantage in this respect silicon especially is a domain where to quote andy jassy there is no compression algorithm for experience b on the curve matters a lot and the biggest story in my view this past week was the rise of the super clouds in his 2020 book with steve hamm frank slootman laid out the case for the rise of data cloud a title which i've conveniently stolen for this breaking analysis rise of the super cloud thank you frank in his book slootman made a case for companies to put data at the center of their organizations rather than organizing just around people for example the idea is to create data networks while people of course are critical organizing around data and enabling people to access and share data will lead to the democracy democratization of data and network effects will kick in this was essentially metcalfe's law for data bob metcalf was the inventor of ethernet ethernet he put forth that premise when we we both worked or the premise when we both worked for pat mcgovern at idg that the value of a network is proportional to the square of the number of its users or nodes on the network thought of another way the first connection isn't so valuable but the billionth connection is really valuable slootman's law if i may says the more people that have access to the data governed of course and the more data connections that can be shared or create sharing the more value will be realized from that data exponential value in fact okay but what is a super cloud super cloud is an architecture that taps the underlying services and primitives of hyperscale clouds to deliver incremental value above and beyond what's available from the public cloud provider a super cloud delivers capabilities through software consumed as services and can run on a single hyperscale cloud or span multiple clouds in fact to the degree that a super cloud can span multiple clouds and even on-premises workloads and hide the underlying complexity of the infrastructure supporting this work the more adoption and the more value will be realized now we've listed some examples of what we consider to be super clouds in the making snowflake is an example we use frequently frequently building a data cloud that spans multiple clouds and supports distributed data but governs that data centrally somewhat consistent with the data mesh approach that we've been talking about for quite some time goldman sachs announced at re invent this year a new data management cloud the goldman sachs financial cloud for data with amazon web services we're going to come back to that later nasdaq ceo adina friedman spoke at the day one keynote with adam silipsky of course the new ceo of aws and talked about the super cloud they're building they didn't use that term that's our term dish networks is building a super cloud to power 5g wireless networks united airlines is really in my view they're porting applications to aws as part of its digital transformation but eventually it will start building out a super cloud travel platform what was most significant about the united effort is the best practices they're borrowing from aws like small teams and moving fast but many others that we've listed here are on a super cloud journey just some of the folks we talked to at reinvent that are building clouds on top of clouds that are shown here cohesity building out a data management cloud focused on data protection and governance hashicorp announced its ipo at a 13 billion valuation building an it automation super cloud data bricks chaos search z-scaler z-scaler is building a security super cloud and many others that we spoke with at the event now we want to take a moment to talk about castles in the cloud it's a premise put forth by jerry chen and the team at greylock it's a really important piece of work that is building out a data set and categorizing the various cloud services to better understand where the cloud giants are investing where startups can participate and how companies can play in the castles that are being built that have been built by the hyperscalers and how they can cross the moats that have been dug and where innovation opportunities exist for other companies now frequently i'm challenged about our statements that there really are only four hyperscalers that exist in the world today aws microsoft google and alibaba while we recognize that companies like oracle have done a really excellent job of improving their clouds we don't consider companies like oracle ibm and other managed service providers as hyperscalers and one of the main data points that we use to defend our thinking is capex investment this was a point that was made in castles in the cloud there are many others that we look at elder kpi size of ecosystem partner acceleration enablement for partners feature sets etc but capex is a big one here's a chart from platform nomics a firm that is obsessed with cl with capex showing annual capex spend for five cloud companies amazon google microsoft ibm and oracle this data goes through 2019 it's annual spend and we've superimposed the direction for each of these companies amazon spent more than 40 billion dollars on capex in 2020 and will spend more than 50 billion this year sure there are some warehouses for the amazon retail business in there and there's other capital expenses in these numbers but the vast majority spent on building out its cloud infrastructure same with google and microsoft now oracle is at least increasing its cap x it's going to spend about 4 billion but it's de minimis compared to the cloud giants and ibm is headed in the other direction it's choosing to invest for instance 34 billion dollars in acquiring red hat instead of putting its capital into a cloud infrastructure look that's a very reasonable strategy but it underscores the gap okay another metric we look at is i as revenue here's an updated chart that we showed last month in our cloud update which at the time excluded alibaba's most recent quarter results so we've updated that very slight change it wasn't really material so you see the four hyperscalers and by the way they invested more than a hundred billion dollars in capex last year it's gonna be larger this year they'll collectively generate more than 120 billion dollars in revenue this year and they're growing at 41 collectively that is remarkable for such a large base of revenue and for aws the rate of revenue growth is accelerating it's the only hyperscaler that can say that that's unreal at their size i mean they're going to do more than 60 billion dollars in revenue this year okay so that's why we say there are only four hyperscalers but so what there are so many opportunities to build on top of the infrastructure that the three u.s giants especially are building as folks are really cautious about china at the moment so let's take a look at what some of the companies that we've been following are doing in the super cloud arena if you will this chart shows some etr data plotting net score or spending momentum on the vertical axis and market share or presence in the etr data set on the horizontal axis most every name on the chart is building some type of super cloud but let me start as we often do calling out aws and azure i guess they're already super clouds but they're not building necessarily on top of of of other people's clouds and there are a little bit you know microsoft does some of that certainly google's doing some of that amazon really bringing its cloud to the edge at this point it's not participating in multi-cloud actively anyway aws and azure they stand alone as the cloud leaders and you can debate what's included in azure in our previous chart on revenue attempts to strip out the microsoft sas business but this is a customer view they see microsoft as a cloud leader which it is so that's why its presence on the horizontal axis and its momentum is is you know very large and very strong stronger than even in aws in this view even though it's is revenue that we showed earlier microsoft is significantly smaller but they both have strong momentum on the vertical axis as shown by that red horizontal line anything above that remember is considered considered elevated that 40 percent or above now google cloud it's well behind these two to we kind of put a red dotted line around it but look at snowflake that blue circle i mean i realize we repeat ourselves often but snowflake continues to hold a net score in the mid to high 70s it held 80 percent for a long time it's getting much much bigger it's so hard to hold that and in 165 mentions in the survey which you can see in the inserted table it continues to expand its market's presence on the horizontal axis now all the technology companies that we track of all of them we feel snowflake's vision and execution on its data cloud and that strategy is most is the most prominent example of a super cloud truly every tech company every company should be paying attention to snowflakes moves and carving out unique value propositions for their customers by standing on the shoulders of cloud giants as ceo ed walsh likes to say now on the left hand side of the chart you can see a number of companies that we spoke with that are in various stages of building out their super clouds data bricks dot spot data robots z z scalar mentioned hashi you see elastic confluent they're all above the forty percent line and somewhat below that line but still respectable we see vmware with tanzu cohesity rubric and veeam and many others that we didn't necessarily speak with directly at reinvent and or they don't show up in the etr dataset now we've also called out cisco dell hpe and ibm we didn't plot them because there's so much other data in there that's not apples to apple but we want to call them up because they all have different points of view and are two varying degrees building super clouds but to be honest these large companies are first protecting their respective on-prem turf you can't blame them those are very large install basis now they're all adding as a service offerings which is cloud-like i mean they're behind way behind trying to figure out you know things like billing and they don't nearly have the ecosystem but they're going to fight rightly they're going to fight hard and compete with their respective portfolios with their channels and their vastly improved simplicity but when you speak to customers at re invent and these are not just startups we're talking to we're talking about customers of these enterprise tech companies these customers want to build on aws they look at aws as cloud and that is the cloud that they want to write to now they want to connect they're on-prem but they're still largely different worlds when you when you talk to these customers now they'll fully admit they can't or won't move everything out of their data centers but the vast vast majority of the customers i spoke with last week at reinvent have much more momentum around moving towards aws they're not repatriating as everybody's talking about or not everybody but many are talking about and yeah there's some recency bias because we just got back but the numbers that we shared earlier don't lie the trend is very clear now these large firms that we mentioned these incumbents in the tech industry these big enterprise tech giants they're starting to move in the super cloud direction and they will have much more credibility around multi-cloud than the hyperscalers but my honest view is that aws's lead is actually accelerating the gap in my opinion is not closing now i want to come back and dig into super cloud a little bit more around 2010 and 2011 we collaborated with two individuals who really shaped our thinking in the big data space peter goldmaker was a cell side analyst at common at the time and abi abhishek meta was with bank of america and b of a was transforming its data operations and avi was was leading that now peter was you know an analyst sharp and less at the time he said you know it's going to be the buyers of big data technology and those that apply big data to their operations who would create the most value he used an example of sap he said look you you couldn't have chosen that sap was going to lead an erp but if you could have figured out who which companies were going to apply erp to their business you would have made a lot of money investing so that was kind of one of his investment theses now he posited that the companies that would apply the big data technology the buyers if you will would create far more value than the cloud errors or the hortonworks or a collection of other number of big data players and clearly he was right in that regard now abi mehta was an example of that and he posited that ecosystems would evolve within vertical industries around data kind of going back to frank slootman's premise that in putting data at the core and that would power the next generation of value creation via data machine learning and business transformation and he was right and that's what we're seeing with the rise of super cloud now after the after the first reinvent we published a post seen on the right hand side of this chart on wikibon about the making of a new gorilla aws and we said the way to compete would be to take an industry focus or one way to compete with take an industry focus and become best to breed within that industry and we aligned really with abbey meta's point of view that industry ecosystems would evolve around data and offer opportunities for non-hyperscalers to compete now what we didn't predict at the time but are now seeing clearly emerge is that these super clouds are going to be built on top of aws and other hyperscale clouds makes sense goldman's financial cloud for data is taking a page out of aws it's pointing its proprietary data algorithms tools and processes at its clients just like amazon did with its technology and it's making these assets available as a service on top of the aws cloud a super cloud for financial services if you will they are relying on aws for infrastructure compute storage networking security and other services like sagemaker to power that super cloud but they're bringing their own ip to the table nasdaq and dish similarly bringing forth their unique value and as i said as i said earlier united airlines will in our view eventually evolve from migrating its apps portfolio to the cloud to building out a super cloud for travel what about your logo what's your super cloud strategy i'm sure you've been thinking about it or perhaps you're already well down the road i'd love to hear how you're doing it and if you see the trends the same or differently as we do okay that's it for now don't forget these episodes are all available as podcasts wherever you listen all you do is search breaking analysis podcast you definitely want to check out etr's website at etr.plus for all the survey data remember we publish a full report every week on wikibon.com and siliconangle.com you can email me if you want to get in touch with david.velante at siliconangle.com you can dm me at devolante on twitter you can comment on our linkedin posts this is dave vellante for the cube insights powered by etr have a great week stay safe be well and we'll see you next time [Music] you