Okay. Welcome, everyone. Welcome to the WANdisco full-year 2020 results presentation. On the call today, we have David Richards, CEO and Co-Founder, and Erik Miller, CFO. What we'll do is we'll run through the presentation with David and Erik. For those of you on the call, you can ask a question through the Q&A box in the Zoom window at the bottom of your screens. Alternatively, raise your hands. We'll take priority from those who write written questions first, and then we can move to those who raise their hand, and we can try and unmute you and get you onto the call. As of now, handing over to David to take you through the presentation. Thanks, Daud. As Daud mentioned, this is David Richards. I'm the Co-Founder and CEO of WANdisco. I'm actually in our Sheffield office today. I'm the only person here, as in this new world that we live in. Hopefully this is going to run very smoothly. It's our full FY 2020 results. In terms of agenda, I'm going to go over the strategic and financial highlights, the opportunity that we see ahead of us with Microsoft Azure, go through some recent case studies. Erik's going to cover the FY 2020 financial results, then hand back to me for outlook and summary. As Daud mentioned, then Q&A, and feel free to ask questions in the Q&A box. In terms of our primary strategic goal, as many of our shareholders will know, associated with fortifying the Microsoft partnership with a go-to-market launch and metered billing in Q4, appearing as a deeply embedded native Azure application. That obviously was key to our strategy moving forward to transition from an enterprise software company to a cloud service company. As part of this, we saw joint blogs, from Microsoft, were part of the data lake migration program, a featured app in the portal, and they made it very clear that this is their preferred migration solution. We're jointly targeting migration of over 100 petabytes of data in FY 2021. You'll be pleased to see later in this presentation, I'll be going over some of the progress that we've made over the past 12 months, in regard to that goal. We also launched LiveData Migrator on Amazon Web Services on the AWS platform in September 2020. We launched this with GoDaddy and achieved migration competency status, which means that we are also a preferred app on the AWS Marketplace. We've got a funded joint marketing program currently happening with AWS, and we're very pleased with the progress that we're making there. We're the chosen migration solution for EMR, which is the Enterprise MapReduce or the Hadoop technology built into the AWS cloud. We're targeting migration of over 30 petabytes of data in FY 2021. We're also, behind all of this, expanding SI system integrator relationships, including Mphasis. We also see a growing opportunity in artificial intelligence and machine learning with Databricks and Snowflake, and those familiar with the U.S. markets will know the performance of those companies has been extraordinary over the past couple of years. Financial headlines. We've obviously got a robust balance sheet to accelerate the conversion of pipeline into revenue. Revenue for 2020 was down on prior year as we revised expectations associated with the launch of the metered billing applications that I mentioned earlier. The statutory loss from operations was up from GBP 28 million-GBP 34 million. Reflection, of course, of the lower revenue in the period and increased cash overheads as we went to market with our new products. We do have a strong balance sheet to accelerate the conversion of this cloud opportunity. The cash reserves of over $55 million at the 30th of April, and virtually no debt following the $42.5 million fund raise we did post period end just a couple of months ago. We, to reiterate, continued broad confidence in outlook, restating our target to deliver at least GBP 35 million in revenues in financial year 2021. In terms of cloud platform system integrators, data and AI ISVs, our unique capabilities have been recognized across the whole ecosystem. In terms of cloud platforms, Azure, as I mentioned, we have a deep integration, one of the only third-party applications to be delivered as a native service on Azure. AWS was the first migration vendor to receive competency, with a funded joint marketing program. We're also going to start talking about Google Cloud Platform. We are seeing demand for this, and we do have resources now to support that platform, and that's in progress. In terms of data and AI ISVs, we'd already talked in the past about Databricks, and we have a LiveData Platform plugin, which is going to be available in the second half of the year. That's approaching preview very soon. Snowflake, we announced a strategic partnership with Snowflake recently. We're looking at Pipeline very closely jointly with them at the moment, and a plugin is currently being developed for our applications. We are seeing demand for Snowflake, and we do have existing customers who also need integration with Snowflake, the data warehouse that Snowflake provide. In terms of system integrators, I've already mentioned Mphasis as a key global SI relationship. They were Microsoft's SI of the year last year. In terms of data and AI specialists, companies like Neudesic, MotiveWorks, and Avanade already have public applications powered by our technology available in the Azure Marketplace. We talk about being positioned for growth and the four P's, product, partnerships, promotion, and priorities. Product. In order to do this, we had to launch a self-serve automated data migration tool, and that's coming from a background of being a traditional enterprise software vendor with POCs and handheld white glove service. We had to reverse that and become a turnkey solution. We launched that in Q4, and that was absolutely a critical stepping stone in transitioning from enterprise software to a native cloud business that we keep talking about. In terms of partnerships, well, the largest cloud platforms, AWS and Azure, the analytics-focused SIs and the largest cloud analytics services in terms of Snowflake, Databricks, Azure Synapse, Azure HDInsight, which is the Hadoop implementation, AWS Glue and EMR that I talked about earlier, all recognize the need to move data at scale on-premises data lake into the cloud, and only WANdisco's technology is able to do this. You'll see a customer reference who moved over 13 petabytes, that I know some of you were present at the Dallas event a week or so ago, would have heard, the VP from that company talk about this publicly. From a promotion perspective, from leading cloud vendors and SIs giving us instant market presence, talking about this being the preferred solution for data migration. Why are they doing this? Well, for every dollars spent with WANdisco represents a 10x- 20x financial gain for vendors. The likes of Databricks and Snowflake need data to power their applications. As I mentioned earlier, the way in which they get that data at scale is using WANdisco. Excuse me. Priorities. Our primary focus is to accelerate the conversion of 130 petabytes of data from on-premise Hadoop systems into the cloud. That's critical for us to meet our objectives this year. The Azure opportunity is really just beginning. When we talk about the only solution to migrate at petabyte scale, we had one of the largest companies, the largest telecommunications company, actually, in the U.S. The VP of their cloud application infrastructure was asked the question, "Why did you choose WANdisco? Why did you pick this particular piece of technology to move this 13 petabytes of data?" This is a transcript of what they said. They looked at a lot of different technologies. What they needed was a tool that could move data reliably at scale. They had 13 petabytes of data in this data lake. There are a lot of companies that can deal with terabytes of data, the small data sets, but they needed a solution that could do this at volume and in less than a year. As they say here, I have to credit WANdisco because they didn't believe that this could be possible at this kind of scale. I think we're already more than 50% of the way through moving that data set in about half the time that they imagined it could be done. This is a brilliant example of a company who had a massive strategic objective to move mission-critical data, business-critical data on-premises to the cloud without any business interruption. Given the size of this company and the importance of this data, I think this is a really good customer example. This is actually a look through the window. We talk about IT modernization and how cloud is going to change everything. You can see here just the impact that the cloud is having on these companies. In the table to the right-hand side there, you can see the former technologies that they had. You can see Hadoop and Teradata, Vertica, the traditional data warehouses, and you can see the technologies that are now being adopted. For raw data, for unstructured data, that data's going to go primarily from Hadoop to Databricks running in cloud. For self-service deep insights, Palantir-based technology, and the data warehouse, of course, is Snowflake. You can see that really that is the software stack moving forward. The really nice thing about this customer is they're looking beyond just the initial migration into the cloud. At WANdisco, we talk about the three phases of enterprise cloud adoption, the initial move into the cloud, keeping the data in sync so they can gradually move application infrastructure from on-premises to the cloud. Then finally, our goal, of course, is to become the broker of data between clouds. You can see here very early in that cycle, we can see customers already looking to move data between Azure and AWS for Databricks and Snowflake. That is already happening today. We're obviously at WANdisco delighted about this because we're already designed into that architecture as they move from on-premises to cloud and then between clouds. We think it's unlikely that any particular company will adopt a single cloud strategy, as they may have done in the past with relational databases and so on. Multi-cloud is certainly going to be a thing, and they're going to arbitrarily decide to run compute applications, which is going to be one of the biggest fixed costs between different clouds arbitrarily. This arbitrage is definitely going to happen. We like the fact that WANdisco is the broker, the sole broker of that data between those clouds. Some feedback from Azure. Again, some important proof points. Turnkey solution, that means that you can begin the migration in minutes. It's the preferred solution, they very rarely say that, if ever, for Hadoop to Azure, that's data lake to their cloud migrations. Really the key point of the relationship with Microsoft is that the LiveData Platform for Azure appears on the same monthly consumption bill as all of their other Azure purchases. There's no friction in the relationship here with the customer. The customer is just using their existing purchasing relationships with the cloud vendor, and they may have large commit to consumes. In the case of some customers like, big pharmaceutical company has $1 billion commit to consume, a large telecommunications company has a $2 billion commit to consume. They can use that commit to consume against the procurement of WANdisco technology. You're going to see us talk about consumption, which a lot of these successful companies are doing. I'll talk about that later in the presentation. In terms of the Hadoop migration program, which they launched, you can see here another proof point from Priya. Who's the VP of Data and AI at Microsoft. Talking about modernizing Hadoop workloads as you saw from one of the prior slides. This all sounds good, but migrating data is going to be impossible. That's not true, according to Microsoft. With WANdisco's LiveData Platform for Azure, you can migrate production data from on-premises to big data platforms, Azure Data Lake Storage with no application downtime or risk. That really is the key, that WANdisco can do this at very low risk and latency. Again, some supporting quotes. Very nice support here from Merv Adrian, who is the lead analyst in data analytics at Gartner. LiveData's ability to move petabytes of data without interrupting production and without risk of losing data mid-flight is something that no other vendor does. I think they call that the silver bullet. Johnson Controls, another recent public customer example, who've been migrating data to the cloud, to Azure using the LiveData product from WANdisco. We also talk about the importance of the last mile. It's not just about moving data on-premises to the cloud, it's also about turning on the lights of these other services. We talked about some of them earlier, HDInsight, Databricks, Synapse, and Snowflake are all real examples of, yes, I'm going to move my data to the cloud, but what's the driving force to do that? I'm going to move my data to the cloud really to achieve artificial intelligence and machine learning. That's really why those companies are taking quite large risks to move that data to the cloud. This last mile of transformation is very important. Again, to reiterate that each dollar of WANdisco translates to $ 10-$ 20 of ACR. This, again, is attractive to the whole ecosystem. From an Azure seller's perspective, why do they care about WANdisco? It accelerates the Azure consumed revenue for them, and they can use it against their MACC program, which is the commit to consume program. It also enables ACR by solving the data gravity problem. Wherever data lies is where the applications will live, and we can do this at a predictable time and cost. We can tell somebody exactly how much it's going to cost and exactly when the migration is going to be finished, like the example with the customer I used earlier. From a global SI perspective, well, it's the fastest time to value. SIs really make money when they're building artificial intelligence and machine learning applications, not lifting and shifting data on-premises to the cloud and other platform services. Again, it's the fastest time to value at a predictable time and cost. That's why Databricks and Snowflake care about WANdisco. I'm going to hand over to Erik now, who's going to talk about the financials. Great. Thanks, David. This all has to be viewed in the context of what we set out to achieve in 2020, and that's to go to market with, and market ready with Microsoft, which we achieved. We emphasized going to market and that's had some effects on recognized revenue being off to $ 10.5 from $ 16.2 in the prior year. Cash overheads rose to $ 36.9 from $ 31.7, based upon the investments we've made in engineering and go-to-marketing resources. That manifests itself in a greater EBITDA loss. Good cash balance prior to the fundraise of $21 million, and after the fund raise, $ 55.3 million at the 30th of April. Just a few days ago. Next slide, please. In the revenue side, just to unpack that a little bit, our big data revenue actually grew 18%. Some of the larger ALM, which is the earlier products we had, Application Lifecycle Management, in 2019 didn't repeat in 2020, and that's somewhat by design. Our future is big data and moving data to the cloud. That was a pleasing result. Cost of sales are off a little bit based on lower revenues. We're still a high gross margin product company, in the 90 some odd percent range, and that's linked to the leverage of how we go to market. Cash overheads, as we discussed, were about $37 million versus about $32 million. Those were on plan. Our headcount, we ended at 180 at the end of December, up from 162 in the prior year. For this year, we're looking at about $ 44 million in cash overheads, all the increase going into engineering and go-to-market resources, and a head count between 200 and 220 people. Going to the balance sheet or summary cash flow, just looking at that. Good balance sheet based on the fundraise we did during that year and the fundraise we did post-period end of $55.3 million. We are well capitalized to attack the mission that we have, and that's to go to market with Microsoft and AWS. Turning to the balance sheet. Strong balance sheet, no bank debt as of April 30th. Very little on this as of the end of the year. A good, strong cash position at present of $55.3 million. Pretty much results as anticipated and as we discussed earlier. Next. We've just completed a successful fundraise to strengthen the balance sheet. What are we going to go off and do with that? We're going to continue to invest in the go-to-market with Azure, AWS, further on in the year, GCP, and build specialist teams to go after the machine learning, artificial intelligence such as Databricks and Snowflake, who we have a relationship with. To continue to widen the relationships with system integrators who are building migration practices around our technology. We've begun to hire sales specialist teams for Azure and AWS. That's going to extend into building the teams to go off with the machine learning AI folks and to do a few tweaks to engineering to make that a more seamless experience. We're going to also accelerate working with the third big cloud provider in the U.S., Google Cloud Services, and increase field enablement for SIs as they begin to add resources to build that out, that migration practice. One of the things we're considering, and we believe having a strong balance sheet is a prerequisite to doing this, is looking at a potential dual listing on a U.S. exchange, to better position the company with our commercial partners. The bulk of our commercial partners are all based in the U.S. That gives a vote of confidence to the company to see it listed. That will be done at the time when we believe market conditions and the company's positioned properly. With that, I'll give it back to David. Thanks, Erik. Outlook and summary. We've talked about the enormous TAM associated with data movement on-premises to cloud and Live Data Migrator, specifically the product. That TAM is $ 50 billion-$75 billion. Where does that come from? When we did the work on TAM with Microsoft, they estimated 200 exabytes-300 exabytes of on-premise analytical data that will have to move to the cloud. I don't think there's any question that that is also growing somewhat exponentially as we speak, as that data remains on-premise and has not yet moved to the cloud. Obviously we got partners heavily incentivized to move this with that 10x-20x revenue multiple that they see by moving that data versus WANdisco to the cloud. Our target specifically this year, over 100 petabytes of data with Azure and over 30 petabytes of data with AWS. That takes WANdisco's FY 2021 target to $35 million, which is a $ 350 million-$700 million opportunity for our partners. Obviously that excludes what I showed you earlier with cross-cloud or cloud-to-cloud data movement. Breaking data between clouds is on top of that from an artificial intelligence and analytics perspective. Pivoting to a consumption-based model, and some of you may who follow Azure and Snowflake, Databricks, AWS, and so on, will be very familiar with this. Consumption really is true SaaS. This is where you look at the way in which, and the degree to which the product is actually being used. I'll come to the differences between what used to be a traditional subscription model versus consumption in a second. All services in the cloud fabric are using a consumption-based approach. I'll explain why in a second. In this world, product and pricing are key. This is not just a change in which companies change their business model. It actually affects the entire company. When we talk about that turnkey experience that customers have to have, a traditional enterprise company really struggles because you need a turnkey experience, you need full cloud integration, you need billing, as you move to this consumption model. The culture focused on driving lifetime value is very important. Our sales compensation model has to move to consumption, and we are looking for those consumption, 100 petabytes of data, in Azure, for example, is our consumption goal for this year, and revenue then falls out of that obviously. We are heavily incentivizing net new logos because that 100 PBs of data represents around 50 customers. We are incentivizing our sales organization heavily to achieve more, a lot more than 50 net new logos this year, as we call it. The product evolution, I've already talked about that. We have to be driven by data consumption, which is a far more agile model. From a customer lifecycle management, we need data on how a customer is actually using the product, which drives interaction with customer success. It's not just sales, it's customer success. We have to ensure that companies are actually using the product. What is the change? When I have this conversation, I have this conversation a lot with people. Most of us believe that the thing that changed with cloud was just this elastic infrastructure that gives us tremendous scale. What they actually possibly don't realize is the thing that has changed is the business model that underlies this, and it was started by AWS, actually. What used to happen, let's think about it, right? The enterprise software company would turn up, they would do a three-month or two-month, and we used to talk about those 90-day sales cycles. They would turn up and do an elongated POC with a company. Now, why would they have to do an elongated POC? Because the risk of whether that product worked or not was with the customer, because the customer would sign up for an upfront two, three, four, five-year deal and pay upfront for the use of their product. While actually only 50% of those were perceived to be successful and 30% would go on to be used in production. In a consumption model, the risk is with the vendor, because if the customer doesn't like it, they just click it off, they turn it off and they stop consumption. This is much better for customers, and we are seeing customers only really want to license software moving forward on a consumption basis. Consequently, the POCs, if you've got the product that can do it, if you've got a turnkey product that can be pressed on in a few minutes, then those POC cycles are very short and they continue to use it because they're using it in a production context if it works. The example I used earlier, the 13 petabytes, they started to use the product for a few terabytes of data and just left it turned on to move the rest of that data. In a subscription basis, well, these POCs have to be long because they have to be certain that it's going to work or the perception that it's going to work. How does the contract work? Well, in a consumption model, it's metered. It's true SaaS. What often happens after a period of time is there is an agreed commit to consume, but the discounting on a commit to consume is nothing like the discounting that you would see from a typical software company on an elongated upfront subscription agreement. In a subscription, of course, it's a flat rate, it's an upfront agreement, and you often see discounting in the 50% range for those larger deals. You do not see that in consumption ever. From a software perspective, it's got to be self-service. It must provide immediate value versus heavy services and a consultative sale. Revenue predictability, what you actually get is hugely predictable revenue through cohort analysis. You get a large number of companies using your product, and you can see that with AWS, with Azure, and obviously the market loves Snowflake because of this. In subscription, of course, it's lumpy. You do big deals on an unpredictable basis. What's the sales process? Well, our guys have to drive POCs. They have to drive people to start using the product, versus in a subscription where it's more selective. That really is the definition of how cloud, native cloud services license and go to market with their product. We're no different. That's exactly what we're doing. The benefits of this, it gives us increasingly reliable and predictable revenue streams. Our customers are enabled to increase consumption at will, you often see far greater consumption than you would ever believe. Certainly historically, with companies that start off with consumption and then move to a commit to consume later. We're selling our service, and our customers want to buy is aligned to the models of industry leaders such as Databricks and Snowflake. As I mentioned, a significantly lower level of discounting versus subscription. How are we doing? Well, we've seen a doubling of pipeline, you can see why we're talking about pipeline, given we're driving POCs and continued use of the product. If you look at those key inflection points, private preview with Azure was launched in February. We saw about 140, 150 deals in pipeline to the limited public preview where people began to see the product that was approaching 200. When public preview was launched, we saw an exponential growth, and that trajectory's continued, I'm pleased to say. Well over 200, approaching 300 opportunities, qualified opportunities in pipeline. You can see how quickly this can move as companies, as turnkey experience, product turns on, people start using and consuming. In summary, we've covered the four Ps. We're positioned to convert 130 petabytes plus in FY 2021. We've got the products. We've launched a self-serve automated data migration tool in Q4. That was a critical stepping stone, deeply embedded into the AWS and Azure clouds, analytics-focused SIs, and Snowflake, Databricks, Synapse, Azure HDI, AWS EMR, all recognize the value of this technology. It's from a promotion perspective, Azure talking about this as their preferred migration solution. From a prioritization perspective, we're laser-focused on moving that 130 petabytes. As we look out into 2021, the shift to consumption, where revenue's recognized over the time that the product's used rather than upfront, people will be used to revenue scaling over the year. To map pipeline progress to scaling revenue. We're going to provide three KPIs that we think are very important. I talked about the number of new logos, the number of new customer wins, the notional MRR, monthly recurring revenue, metered plus an estimate of subscription revenue as MRR. We're going to normalize that data for you that will help build models around the company. The retention rate, so the percent of customers using the product versus those using the product a year earlier. We would expect to see companies continue to use that product. We've certainly seen evidence of that so far. Based on migrating 100 petabytes of data on Azure, circa 50 customers, 30 petabytes on AWS, 15-20 customers in 2021, we believe that revenues in 2021 will be at least $35 million. With that, I'll hand back to David Richards for Q&A. Okay. We'll start the Q&A session. Give you a minute or so to either raise your hands or type in a question on the chat box. If you're on the phone, then it would be a raising of hand. If you're on the Zoom call, then you can type in or you can raise your hand. Got a couple of raised hands. First one is George. I'm about to unmute you so you can ask your question. Go ahead. Well, hi there, thank you very much for taking my call. A few quickies from me, if you wouldn't mind. Large customers clearly love you. That's the message coming out. When you think about TAM, is there any issue that you really appeal in terms of your sweet spot to these larger people, sort of, 10 + PB kind of customers, and that although you look at a very large addressable market, really your opportunity set is much narrower within it. Secondly, if you wouldn't mind, really like what you're saying about the migration from subscription to consumption. The downside though is that it does impact cash. You move from prepay to postpaid. Does that have any sort of deeper implications in terms of your cash burn? Thank you. I'll start off and then maybe Erik can finish. In terms of customer size, I think the size of the initial customers who took on the product was a legacy from us being an enterprise, traditional enterprise software vendor, just like most of the companies that you follow, George, and I'm sure other people do as well. We are still very appealing to very large companies, but there's an awful lot of data in companies of all different shapes and sizes. The new service that we launched in Q4, you will see a lot more, and we are already seeing a lot more of those 300 or so that we saw at the end of last year, opportunities in pipeline. They were all sorts of different shapes and sizes. You're going to see a transformation as we move to consumption and cloud service of that change. In terms of cash consumption, what you will see happen in a consumption-based model is the POC timeframe is considerably shorter, because the POC really involves using the product and beginning consumption much earlier in the cycle than you would see in a traditional enterprise software business. We don't think that there is going to be too much of a lag in revenue. Obviously, it gets consumed over time, but certainly, we're confident on that. Erik, do you want to add anything else to it? It does shift cash flows a bit into the future. That's typical that one would see in that effect. As David mentioned, it does accelerate time to revenue. These things pay on a 30-day cycle on metered revenue. Once we get a reasonable cohort with that, one of the thinking between raising as much money as we did is to buffer that until that really gets going. We think that's a shorter-term phenomenon when we build the cohort of renewals as we go forward. I think it dampens out in the wash after about the first year, honestly. I think we're in good shape with that. Thank you. Thanks, George. There is some questions on the chat which I'm going to amalgamate a couple of them, which both talk about the same thing. Any idea, I guess, for Erik, any idea around H1, H2 weighting to get to the $ 35 million? Probably a 30/70 split because of the way that it builds and pipeline conversion for this year. It'll be back-end loaded for the year. Typical enterprise cycle with the subscriptions ramping, that's just sort of a natural mathematical effect. Okay. We have another question, live question from Andreas. I'm going to unmute you, Andreas, if you want to ask your question. Yes. Hello, guys. Can you hear me now? Yes. Yeah, Andreas. Perfectly. Okay, two questions from me here. Now you're more than four months into the year already. You talk about 50 customers with Microsoft and 15 with AWS. Can you kind of tell how you feel about that, you are 1/3 Into the year and how you feel about reaching that, at least so far? Yeah, we have a lot of current companies who are in the process of evaluating the product, turning it on. In order for some to use it, for example, we have deals in South Africa and in Korea and all over the place, actually. The service, and in Canada, for example, had to be turned on in the Azure cloud. I'm not saying that there's a delay because it's now all turned on, but a number of those, we've got a large number of companies currently in the process of turning on and using product, which will then convert into consumption, and we'll be guiding that consumption in due course. In terms of the key metrics that we look at in feeling comfortable with that number, it's basic pipeline analysis. We have a lot of opportunities brought to us from Microsoft, AWS, Databricks, and now Snowflake as well, and we have more than enough in pipeline in order to achieve our goals this year. Okay. You saw the slide there you shown when your kind of opportunities that keep going up and up and up, are you disappointed with the conversion of that opportunity or do you feel that it's in line or? No, we're in line. We, for example, ran a training session and five banks, I think, turned up to that training session, all in the process of turning on product. This was just an open training session. Yes, we're very happy with progress. Okay. The second question is, AWS and Azure, they have around, I think, 2,000 salespeople or something each year. Snowflake and Infosys and all those have a lot of salespeople. I think last time we talked half a year ago or something, you talked about you guys being an IP licensing, like a royalty model on- It seems like you have reversed a little bit now you talked about hiring salespeople yourself and building that up. Can you maybe elaborate on that change? No. There's no change to the model. We call them specialist sales, because we don't want to hire a bunch of biz dev people. What we need is to manage 2,000, actually, it's more than 2,000. There are 2,000 specialists at Microsoft, but there are over 20,000 sellers. We are in the process of hiring very senior, well-seasoned salespeople from those companies, actually, who are very interested in joining WANdisco, which is a very good sign, in order to manage those channels. Think of them more as channel managers. They do pipeline reviews. They sit down with Azure sellers and look at opportunities and so on, and make sure that WANdisco is baked into those solutions that they are currently proposing to customers. Okay. It's not really salespeople, it's more like managers you're hiring. Yeah. We've got two sides to our sales organization. There's direct selling. We're not gonna be expanding that. We are hiring people to sit inside the channels to ensure that our products are sold by Azure, AWS, Databricks, and Snowflake sellers. Okay. That's everything I have for now. Okay. Okay. Thanks, Andreas. If there's any more questions, then please type them into the box, or raise your hand. Currently don't have any other questions. Give a little bit more time for people to raise their hands or type. There's a raised hand. I don't know whether that's a follow-up question from George or the same question he had before. We're just gonna unmute you, George, in case you had a follow-up. Thank you. I'll ask you the same question again, then. No, I won't. Can you tell us at all the story of the 11 through Q1, sort of the 11 early adopters? What has their consumption been? How much data has moved? What is the attach rate like? It's still early to give you those metrics, George. We will be delivering those metrics in the very near future. It's still a little early for us to feel confident in delivering some of those. I can say that it does look pretty good. A number of those companies were waiting for the service to be turned on by Microsoft into their region, because there are GDPR issues, right? If you're in Canada or in Korea, you have to only run services that are within those clouds within that region, and that's a legal requirement. A lot of those companies were waiting for that to be turned on, which happened two weeks ago. We're still in the midst of untangling all of that lovely data for you. Okay. Great stuff. Do we know what Microsoft's sort of success factors are? Have they given you anything in there? They only care about consumption. Yeah. Every single petabyte of data from that data gravity perspective, they're very focused on that. Success for them would be, well, it's a lot more than 100 petabytes of moved data in our financial year. Yeah. On Snowflake, it's very impressive to see them on the partnership, but we go way back with Databricks, and we're still not seeing meaningful revenue there. How will it be for Snowflake, do you think? I think you're going to see virtually every single deal that we do in Azure be associated with either Azure, Databricks or Snowflake or both. Those relationships are not just nice logos to have, they are absolutely essential for this company. When the Hadoop data moves to the cloud, it is going to go primarily to Databricks. It doesn't just go to the cloud, it goes to something. You will see further announcements, I'm sure, with ourselves, Microsoft and Databricks over the coming weeks and months. Very good. Thank you. Thanks, George. A few questions are coming through the chat box. Can you speak to the opportunities from SI and other channels in 2021 versus what you've identified with AWS and Azure? I think you've partly answered that, David, but maybe broaden the topics around how SIs are helping us would be helpful. Yeah. We've got a lot of SI interest, more than I could even mention on the slides. We will only do or sign deals with SIs, and there are some that we can't announce, if they bring with them a pipeline of opportunities on one of those clouds. That's very important, I think, for everybody to understand that we could do 10 times the number of SI deals than I talked about here. There are two or three that are very interesting, that have strong pipeline, and deals that are either in the midst of consumption or about to start consumption. There's a question around attach rate for LiveData Plane. Any updated thoughts? What I'd say is, Erik, you'd probably agree, that it's early days in terms of moving from LiveData Migrator to LiveData Plane. What we'd normally find is that companies will use LiveData Migrator to move the data, and they'll continue to use LiveData Migrator post the migration, until a point where they actually want to create a bi-directional hybrid cloud environment. It could be up to a year while they're moving applications, for example, maybe even longer than a year while that happens. Far too early to talk about attach rates of LiveData Plane. Probably something that we could report on maybe later in the year or at the end of the year. Yeah. Another question coming in. Have any current pipeline opportunities withdrawn, declined to initiate service? If so, what reasons are they giving for doing so? No. The only delays we've seen is associated with the native service being available in the Azure cloud in those regions. Yeah. That's the only reason. They're now available, and those are all beginning, so. I think, for the audience sake, you really have to understand that moving a data lake into the cloud is a complex process. One part of that process is moving the data, where we're obviously the solution for doing that. For most customers, their considerations around what they do in their extended relationships with SIs or the cloud vendor in terms of the applications they're trying to move or trying to replicate, et cetera, that leads to commitment to the use of WANdisco technology. Because it's a, particularly on Azure, a consumption-based target, it doesn't give you commitment to the exact date which they turn the service on. That's why the data that we'll provide for the first half will be much more relevant than providing it for the first quarter. No more questions as far as I can see, unless you guys can see anything. Nothing in the Q&A box, nothing else in the chat box, no other hands raised. David, do you want to conclude and Yeah. Thanks, everybody. Thanks for the time today. Obviously, the KPIs I think that we talked about today are going to be very helpful for you in the future. Thanks again for all the support. Thanks, guys. Thanks, everyone.