 All right, welcome, everyone. Hello, and welcome to our next EDW session called How Automated Data Lineage Accelerates BI Performance Inside Information from Our Customers. We have David Bitten here. He's the VP of Sales of Octopi. Just wanted to let everybody know, all audience members are muted during these sessions. So please submit your questions in the Q&A window on the right side of the screen. And our speaker will respond to as many questions as possible at the end of the talk. So let's begin our presentation now. Thank you, and welcome, David Bitten. Thank you, John, for that great introduction. Wow, what can I say? I'm both privileged and excited to be here today to also be able to present Octopi to you all. As many of you may know, we've been attending EDW for many years in person. This year, unfortunately, due to the pandemic, we've been forced to attend virtually. Let's hope that this will all be over and behind us by next year this time, and we'll be able to do this in person. So since, as they mentioned, there's a large audience. Their questions, please forward them to us, and I will try and address them at the very end of the presentation. So without further ado, I'll jump straight in. And a little bit about the company. So Octopi was started a number of years ago by our founders, and they actually came from the BI landscape. So they were actually living and breathing the challenges that BI people are breathing and living and dealing with on a day-to-day basis. They were actually leading different groups in different industries. So they had experience in insurance, telecom, health care, and others, where they faced a lot of the same challenges that most of our customers are facing. So to give you an idea of the types of challenges they were facing, they were getting complaints from their business users about data reliability, for example. And the reason for that was because oftentimes they would obtain reports or receive reports, and those reports would oftentimes be inaccurate or corrupt or missing data, have missing data or wrong data. And so it caused them to lose confidence in the data that they were using. And so other issues related to whenever they would touch something, whenever they would create a new business process, edit an existing ETL, change a table, or a view, it would somehow impact other things down the line, such as reports and so on. And then there were other issues just trying to get a handle on where their data was. In order to do that, they needed to dive in and discover the metadata that resided in all of the different systems that they were managing and using in order to move and manage their data. Now, unfortunately, all of this work was being done manually by them. And so these are the same types of challenges most of the customers that we deal with that most organizations are facing with. And so the entire data movement or data lineage process was very challenging for them. And that was the catalyst that led them on a quest to look for a solution for their teams, to help their teams become more efficient, to automate all of the manual work that they were delving in and dealing with on a day-to-day basis. And that would provide a system that would prove, they were looking for a system that would provide them with simple analysis, they were looking for a solution that was simple and easy to use, meaning no manual work, and that would provide fast results from all of the different systems that they were managing. Now, after doing a lot of market research, they realized there was no such thing. And this was a great opportunity that was presented to them. Thankfully, they took advantage of it and created Octopi. Now, although it sounds ambitious, this is exactly the challenges that Octopi was made to address. And as a result today, Octopi is running in many different organizations around the world. So in this slide, you can see a cross-section of our clients. This is a sampling of some of our clients today. We have hundreds of customers, thousands of users, and some of them, as you can see here, I'm sure you might recognize. Now, I wanted to share this slide with you for a couple of reasons. First and foremost is to show you the exponential growth that we've experienced in the last few years, which is simply due to the fact that our product delivers. And second, you can see that Octopi works in just about every vertical or company size. And this is because the only two criteria that Octopi requires is that you use it, or the only criteria is that you lose the technology that we support. So now, when coming to Octopi, just about all of our customers are facing or mentioning, facing the same, following similar challenges. And I'll talk about those in just a few minutes. Now, how do we do what we do? So everything sounds great. Now, with Octopi, all of that metadata that's so crucial for you to understand and so difficult for you to collect is actually collected by us, very easily and placed into a cross-platform SaaS solution. We deliver that, we discover that metadata automatically, which is a key point. I wanna make sure that everybody remembers. It's done automatically, meaning there are no manual processes, there's no documentation required, no prep work, customizations. And we're certainly not sending a bunch of highly-paid professional services in there to do it for you. So the metadata, once it's collected by us, is centralized into that one SaaS solution, a platform on the cloud, of course. It then goes through a bunch of different processes, such as being analyzed, then it gets centralized, first it gets centralized, then it gets analyzed, modeled, parsed, cataloged, indexed, and probably quite a few that I can't even think of right now, but just imagine it's quite a few. And then it's ready for your discovery so that you can easily find metadata literally in seconds by clicking the mouse. So Octopi reduces the time that would normally take to do that, as you can all imagine, it could take days, weeks, possibly longer. And then we also, we reduce that time into seconds, providing you with the best, most accurate picture of your metadata. And so not only is Octopi essentially in that initial setup, collecting cataloging analysis and analysis of your metadata, it's also essential when you move forward, meaning so whenever you need to look for metadata, lineage, for example, may it be today or tomorrow or next week, next month, next year, whenever, you'll always be looking at the most current picture of your metadata at that given point in time. So it won't be some spreadsheet that was created, of course, with all good intentions but unfortunately never updated. A couple of years ago, for example, with Octopi will always be the most current picture of your metadata at that given point in time when you log in. So I'm gonna share this slide for you because this will give you a good idea of some of the use cases that Octopi is essential for. This is what we would call a typical example of a BI infrastructure. It's very common amongst our customers and I'm sure it's very common amongst those listeners and those here present in this presentation. Now on the left hand side, what we can see here, those are the example of the many different business applications that are being used by the various organizations and also the data, actually those business applications are being used by the various users. Those users are entering data in large quantity into those systems. Now, they don't have direct access to that data. Now, it's usually the BI team or the data management team, whatever it's called, it might be called slightly different in your organization but essentially it's the BI team that's responsible for making that data available to those users and so that's why at any given point in time, the team needs to know where the data is and then understand its movement process through the various systems that we see here. So you need to know the intricacies, the dependencies and so on as well. Now, because the metadata is actually scattered throughout all of these different systems, that's actually very challenging to do and so what our customers are telling us is that their groups, those are responsible for managing and moving the data are actually spending more than 50% of their time just trying to understand where the metadata is in order to understand relationships, the connections and the data lineage and of course, we all know that is necessary in order for them to be able to provide the organization with the data that it so desperately needs. So now what we've done in order to overcome these challenges, we've actually leveraged technology with some very powerful algorithms that we've internally developed, the machine learning and the processing power that we have available to us on the cloud to create a solution that actually extracts that metadata, centralizes it into one platform analyzes it and that makes it visually available to you from those various systems. We're able to do it very simply, we extract that metadata from the different tools, that metadata that is uploaded to the cloud for analysis and then within 24 hours, you get an in-depth picture of the entire landscape and it's that simple. And so what that means, no major projects, no major timelines, no major resources, really all you need is one person in about an hour or two to configure and you're good to go. All right, so let's talk about a little bit of some use cases of our customers and how they came to occupy and how we address them. So, first one I'm gonna talk about is a large European bank and asset management conglomerate, you may have heard of them, Bank of Manualatom. So, Manualatom approached us with a database that had no design and they had daily issues with it. They also needed their reports to be trustworthy of course, for obvious reasons and in order to do that, they needed to see where the data was coming from because I can't state this enough. If you don't know where the data is coming from, you can't be certain about that data in that report. And so this was part of their daily routine and since they have many data sources being ingested as well. So they wanted a platform that would help them assess the quality of the data and build their metric. In addition, they needed our help with a migration project to the cloud and needed to redesign their procedures. So now after implementing the Octopi platform, their entire team relies on Octopi to address these processes. Another use case, this one you might be more familiar with, Farm Credit Services America is a financial cooperative with over 72 associations together with that cooperative as part of the cooperative. So FCSA came to us with a challenge they were facing. They had a vendor-driven upgrade that forced them to upgrade their legacy database and this was a recurring project that required huge amounts of manual work. All right, so let's talk a little bit about the issue. So in more detail, the project required mass-scale communications to the users and consumers to try to understand the impact any changes that were being made. So the users were confused and they were unsure of the impact if where the data elements were being used, which also drove more research and legwork to find the rightful consumers. They needed to invest time in manual research which was conducted within internal databases, investigating table references, stored procedures, SSRS reports and so on to determine usage and ownership. Now there was a lot of hunting, pecking, spreadsheets were involved, running down owners and packages and data and so on. And these discovery efforts spanned approximately four months or more and still left unanswered questions lingering in some areas. Lots of key decisions were made just in case and that created a lot of technical debt that they were actually trying to get rid of. All right, so let's talk about now after Octopi. So we offered them of course a streamlined research approach to trace usage and ownership using the discovery model, analysts some new to the association easily went from field to endpoints to quickly understand the usage and take next steps to determine deprecation and impact. Now the lineage model offered greater insight into where changes can cause consuming impacts, streamlined efforts to easily seek comments and code, et cetera and determine potential ownership of stored procedures and load processes. So Octopi reduced or reduced the research time and allowed for greater focus on the impact and solutions to redirect and to minimize and eliminate how to redirect and a solution also to minimize and eliminate a conversion gaps in the project itself. All right, here's another one that might be interesting to you guys. Maurer, it's actually a spelled Maurer but pronounced more investment management limited. There are a privately owned independent international investment firm and they manage approximately 82 billion in assets for individual and investors. So more needed to understand the data in the reports, documents and existing reports and develop new ones as well. And they also needed to design these processes they needed to, in order to design these processes they needed to invest a great amount of work to ensure that the data was not impaired. So by using Octopi they cut the time down that they needed in order to accomplish this by literally in half. All right, so in summary, what we've quickly gone over here today is what our customers are telling us makes us a unique and a unique platform. So we combine three main benefits into one powerful solution. Number one, as you see here on the top is that we are a cloud based solution. So very simple and easy to get up and running very simple and easy to set up literally as I mentioned an hour or two by one person and you're good to go cross platform. What does that mean? We analyze the metadata across all of your different BI systems from source to target and provide you with that lineage and discovery capabilities. And when you will see, when you come visit us for a demo you will see that Octopi is a very simple and easy to use, very intuitive. And what that means is that they're very simple to onboard. Your team can be up and running with Octopi literally in about a half an hour kickoff session. No longer is there that one guru that needs to be appeased with pizza or beer in order to get up to the top of the line in order to get anything done. Your entire team, the entire organization that can gain value by using Octopi can log in and go ahead and get what they need literally in seconds. All right, so now it gives me great pleasure to announce that Octopi introduces the Data Lineage XD, the first solution on the market to provide advanced multi-dimension views of Data Lineage. And so you guys are all asking what does Data Lineage XD mean? And I will explain it to you. So let me explain. So one type of lineage just doesn't cut it anymore. There are three types of lineage that you need. Number one, cross-system lineage provides end-to-end lineage at the system level from the entry point into the BI landscape all the way to reporting and analytics. This level provides a high level visibility into the data flow mapping where data is coming from and where it's going. Second, the inner system lineage details the column level lineage within an ETL process or report or database object, understanding the logic and data flow for each column provides visibility at the column level. So no matter how complex the process is, the report or object, you can understand it. So in end-to-end, number three is end-to-end column lineage which details column to column level lineage between systems from the entry point into the BI landscapes all the way through to the reporting and analytics. All right, so if we've piqued your interest, please reach out to me and we would be happy to introduce you to the next level in data lineage. And here you have my contact information. At this point, what I will do is allow time for some questions. So if you have any questions, I'm gonna take a look at them and see here. Let's take a look and see what we have. All right, so do we have APIs to integrate custom metadata from homegrown systems that do not have a data database, et cetera? So there are two answers to that question. Number one, we have APIs that you can extract metadata from. So it's the opposite of what you're asking for. However, if there are systems that we do not support, we do have manual links that you can actually configure one time and that should be able to address that. All right, it seems like, yeah, the other question. How long does it take to configure Octopi, et cetera? So we've covered that briefly in the presentation. It is telling us, I mentioned that it takes literally about one hour or two for one person to configure. All you're doing is pointing the Octopi thin client to your metadata sources, hit the run button, and that's all that's required. That's basically it. Any other questions? Sure, we have a user asking us how easy is it to use Octopi or to get started using Octopi. Because it's very similar to that. Literally, as I mentioned earlier to get set up and running, we'll take one person about an hour work. That metadata is uploaded to the cloud for analysis. Within 24 to 48 hours, you have a complete clarity into your entire landscape. Thank you very much, everyone. We hope to see you in our booth, our virtual booth, and we hope to be able to schedule some calls with you to introduce you to that next level of data lineage. Oh, okay, here we go. All right, do you have a looker integration? And if not, it is on your own. So currently we do not have it, but it is on our roadmap for this year. Sure, so the data, explain the data lineage, a use case would be helpful. So let's try and explain that a little bit more. All right, so we have a few more minutes. So I will try to answer that question. Let's say, for example, today, someone, Mr. or Mrs. CFO gives you a call and says that there is an issue with a report. It is, for example, the end of the quarter. That report has an error in a field or there is something wrong with that field. It doesn't really matter what the issue is. You need to trace back how the data landed on it. So you need to understand the lineage of that report. And most organizations to do that today probably requires a lot of manual work, which will involve reverse engineering that report manually to try to understand how the data landed on it. With Octopi, you can log in, type the name of the report literally within seconds. You can understand the entire end source to target lineage of that report, either from the system level, as we said earlier, from the three different levels, from the inter or from the actual column to column level as well. Hopefully that answers your questions. What data sources can you use the data lineage tool for specifically looking for AWS sources? So if you log into our website, actually, you know what? Let me see if I can share that screen. I think I can. Currently today, these are the technologies that we support. In general, this is what we would call the BI landscape. You may have many different hundreds, if not thousands of different source applications. Those are still, we can still provide you with a source to target lineage without going into those different systems to extract or analyze the metadata. The way we do it is as soon as that metadata is extracted into one of the supported systems, we can then extract the metadata that we required in order to provide you with that N10 data lineage. All right, so we have a question. How do I visit your booth to discuss this? That's a great question. I'm very new to this platform, but I understand that you can log in and you should be able to find us. I don't know unfortunately how to answer that question to you. I hope that maybe John or Louise will be able to answer that via chat. Other important questions here, how other use cases where Octopi would be essential for of course, Octopi will be essential in many, many different use cases. Let's say you have a migration project, you need to move to the cloud. Of course you need to understand your current assets, where they are and how the changes will impact, any change will be impacting reports and so on. So Octopi will be able to give you that transparency and that lineage and discovery capability to be able to see and do that. Of course, I can demonstrate that much more easier in a demo and I invite you to join to see that. There are of course many, many other use cases providing audit trails for different rules and regulations, impact analysis, where you need to make a change. You wanna know what will be impacted. Of course, there are many, many dozens of different use cases that would be relevant for. All right. Thank you very much everyone once again for joining. I will be logging off shortly, but it will be available in our booth. So if you'd like to chat with me, we'd be happy to take this further. And of course we'd like to invite you to sign up for a demo where we can show you this live in a demo environment. All right. Thank you so much, David. Let's thank David for this great presentation and thanks to our attendees for tuning in. Please complete your conference session survey on the page for this session. The next session will start in about 30 minutes. So please feel free to go ahead and network. And we will see you soon. Thanks again. Thank you everyone.