WEBVTT 00:00:00.000 --> 00:00:20.080 00:00:20.564 --> 00:00:24.464 Hello and welcome, everybody. This is Joe from StartupRate.io, 00:00:24.624 --> 00:00:27.204 your startup podcast and YouTube blog from Germany. 00:00:27.544 --> 00:00:34.564 Today, I would like to welcome Stefan Opitz here, the founder and CEO of the Coderflow GmbH, 00:00:34.784 --> 00:00:40.264 which is a German form of LTD, a groundbreaking SaaS platform that is transforming 00:00:40.264 --> 00:00:42.804 data architecture management. 00:00:43.004 --> 00:00:47.724 With a rich background in IT consultancy and a deep understanding of the challenges 00:00:47.724 --> 00:00:52.644 in data integration, Stefan recognized the limitations of traditional top-down 00:00:52.644 --> 00:00:54.124 approaches to data modeling. 00:00:54.444 --> 00:00:59.144 This insight led to the creation of Codaflow, which adopts a bottom-up data 00:00:59.144 --> 00:01:04.364 modeling strategy, emphasizing granular data level design to automatically generate 00:01:04.364 --> 00:01:07.364 higher-level architecture views. 00:01:07.584 --> 00:01:13.264 And this integrates automated system landscape generation, real-time collaboration, 00:01:13.884 --> 00:01:17.804 integrated change management, and design-first approach. 00:01:17.804 --> 00:01:23.644 Join us as we delve into Stefan's journey, exploring how Codaflow is enabling 00:01:23.644 --> 00:01:27.164 organizations to achieve transparent, collaborative, 00:01:27.784 --> 00:01:31.584 and governed data model design, ensuring seamless integration, 00:01:31.844 --> 00:01:34.424 and minimizing data risks. 00:01:34.844 --> 00:01:38.444 Almost without a mistake, Stefan, welcome from Munich. 00:01:39.901 --> 00:01:43.641 Well, thank you for having me. And actually, I guess we are done now because 00:01:43.641 --> 00:01:46.001 you said everything. So it's absolutely amazing. 00:01:46.281 --> 00:01:49.101 Yeah, we're done. Hey, guys, it was the shortest recording ever. Goodbye. 00:01:49.881 --> 00:01:51.281 Exactly. Glad being here. 00:01:53.101 --> 00:01:57.361 Most efficient introduction ever. Check. Thank you to just me, 00:01:57.481 --> 00:01:59.841 my virtual assistant, who made this possible. Thank you. 00:02:01.541 --> 00:02:08.281 That said, let us talk a little bit about who you are and what you did and how 00:02:08.281 --> 00:02:13.281 you went from consulting to founding Codaflow. 00:02:13.461 --> 00:02:18.901 And then we may already hint to our audience that data architecture, 00:02:19.121 --> 00:02:24.201 data architecture management is a pretty boring data, but it gets very important 00:02:24.201 --> 00:02:27.161 if you want to train an AI on your own data. 00:02:28.861 --> 00:02:34.701 For instance, exactly. Yeah, as you said, actually I'm coming from a consulting 00:02:34.701 --> 00:02:40.801 background and I still run like a very specialized consulting company and background. 00:02:42.221 --> 00:02:47.581 And fun fact is that we actually were looking for a solution first. 00:02:47.761 --> 00:02:51.701 So it's not like that we came up with the, well, let's found Coderflow and let's 00:02:51.701 --> 00:02:53.301 do something completely different. 00:02:53.581 --> 00:02:58.181 It was rather the other way around. So we were looking for solutions in a data 00:02:58.181 --> 00:03:02.961 architecture area because we were facing certain challenges over and over again, 00:03:03.081 --> 00:03:08.501 because we're doing a lot of integration and we're chasing after data like all the time. 00:03:08.781 --> 00:03:14.441 And yeah, at some point, well, we simply said, okay, if there's nothing out 00:03:14.441 --> 00:03:20.181 there which is really satisfying us and everything is usually targeting enterprise level, 00:03:20.461 --> 00:03:26.661 we simply said, okay, well, let's then simply try to disrupt the world and let's 00:03:26.661 --> 00:03:30.101 make it a better place, at least from the point of the data architecture. 00:03:32.861 --> 00:03:36.181 Make the world a better place. Okay, yeah, that's a pretty high goal. 00:03:36.361 --> 00:03:38.781 Yeah, I know. Bold claim. 00:03:40.720 --> 00:03:47.660 Okay, great. You talked about you want to do that stuff yourself. 00:03:47.980 --> 00:03:56.260 Can you give us a little introduction, just a tiny bit on why data architecture 00:03:56.260 --> 00:04:00.020 is important for the companies out there? 00:04:00.380 --> 00:04:05.180 Not the ones who are very tiny and running on one server, but the ones as soon 00:04:05.180 --> 00:04:08.120 as they start growing, especially growing very fast. 00:04:08.360 --> 00:04:12.300 I would even go a little bit further than that. Actually, I believe data architecture 00:04:12.300 --> 00:04:16.100 is important for everyone, and it will become more important. 00:04:16.420 --> 00:04:21.100 But the main challenges we were actually facing is that whenever we came into 00:04:21.100 --> 00:04:28.360 a new client and we were asking for their, let's say, how is your setup running right now? 00:04:28.500 --> 00:04:31.940 And how is your integration working? From a technology point of view, 00:04:32.080 --> 00:04:36.000 they were actually rather, like that was rather a short discussion because then 00:04:36.000 --> 00:04:38.720 you just like show a couple of slides and then that's it. 00:04:38.720 --> 00:04:41.660 But as soon you wanted to actually deep dive 00:04:41.660 --> 00:04:44.600 a little bit into like the details of it like like what 00:04:44.600 --> 00:04:47.480 information is being exchanged where is that actually being 00:04:47.480 --> 00:04:52.140 forwarded to and all that then it was becoming a completely different discussion 00:04:52.140 --> 00:04:55.900 because then people would not be able to answer that and would actually just 00:04:55.900 --> 00:05:01.660 send you somewhere like you just like basically well go away and ask someone 00:05:01.660 --> 00:05:05.340 who knows and then the next question was like well who knows and well 00:05:05.620 --> 00:05:09.860 we don't know but that person might know and then they just like push you like 00:05:09.860 --> 00:05:15.880 basically from door to door and that is i believe one of the main main challenge in general that 00:05:16.810 --> 00:05:22.530 Our IT world becomes more and more a network of different systems. 00:05:23.150 --> 00:05:26.050 I mean, there are studies out there, right, saying like, okay, 00:05:26.170 --> 00:05:28.450 well, in average, it's 112 systems. 00:05:28.470 --> 00:05:31.170 Others say like it's even 200 or even more. 00:05:31.830 --> 00:05:35.810 All of that information is being exchanged. 00:05:36.170 --> 00:05:39.350 And apparently, to my, 00:05:39.550 --> 00:05:42.450 let's say, experience I have never met 00:05:42.450 --> 00:05:45.650 a company who has full control on 00:05:45.650 --> 00:05:48.590 all that and I think that is one of 00:05:48.590 --> 00:05:55.310 one of the the let's say rather infamous elements of data architecture because 00:05:55.310 --> 00:06:00.650 it's always outdated and no one knows and it's even identifying it it feels 00:06:00.650 --> 00:06:06.870 like if you're comparing like this foldable maps for streets to Google Maps, 00:06:07.090 --> 00:06:09.090 right? So it's a little bit like the same way. 00:06:09.370 --> 00:06:15.510 So if you're lucky, you have an outdated plan of the 1970s and you are trying to find your way. 00:06:17.250 --> 00:06:24.370 And personal experience is that in the IT of very large organizations, 00:06:24.410 --> 00:06:29.910 there are usually a handful of people who do have an idea of the general data flows around, 00:06:29.930 --> 00:06:36.910 but it starts to get really tricky if you dive into the details when you want 00:06:36.910 --> 00:06:39.930 to put something together, like a data lake or something, 00:06:40.330 --> 00:06:43.650 where's this data coming from? From this system? No, it's coming from this system. 00:06:43.770 --> 00:06:46.970 No, it's coming from this system. Then it gets real, real tricky. 00:06:47.690 --> 00:06:51.090 When we discussed before, you told me there's a bottom-up approach. 00:06:51.230 --> 00:06:54.130 So what do you do? Do you give a vote to all the bits out there? 00:06:57.170 --> 00:06:58.270 Something like that. 00:07:00.510 --> 00:07:07.750 So, well, bottom-up approach is, and I guess we need to put that a little bit into perspective. 00:07:09.726 --> 00:07:13.646 Common frameworks, common methodologies usually break things down. 00:07:13.946 --> 00:07:18.686 So you start from a very high level, and then you're just breaking it down into smaller pieces. 00:07:19.266 --> 00:07:23.746 And that is something which absolutely makes sense in certain areas. 00:07:23.966 --> 00:07:29.766 And apparently, it has been, let's say, the typical approach for data architecture as well. 00:07:31.346 --> 00:07:35.366 Let's say that is part of the problem from my point of view, 00:07:35.386 --> 00:07:41.846 because when we are talking about data, if you actually talk to a person like 00:07:41.846 --> 00:07:43.746 these experts you were just mentioning, right? 00:07:43.866 --> 00:07:49.686 So if you have such an expert, they usually have deep knowledge on a particular 00:07:49.686 --> 00:07:52.146 system, on a particular data structure. 00:07:52.386 --> 00:07:58.146 It's very rare you find someone who knows all the systems with all their data elements in there. 00:07:58.306 --> 00:08:04.266 It's like I have never met someone, and I don't believe it is humanly possible even to get there. 00:08:05.146 --> 00:08:12.606 For everybody who's now out there smiling, you should once, at least once, 00:08:12.846 --> 00:08:20.066 try to understand those massive databases who only are out there to grasp data flows. 00:08:20.286 --> 00:08:24.986 It turns your head upside down within a few days and after a month, 00:08:25.006 --> 00:08:27.486 you have not fully grasped it. 00:08:28.966 --> 00:08:29.726 Absolutely. 00:08:30.998 --> 00:08:36.358 That's exactly where we are coming from. If you think about this one expert, 00:08:36.558 --> 00:08:39.438 the expert knows exactly what the data structure looks like. 00:08:39.678 --> 00:08:44.238 Quite honestly, data structure is compared to a business process, 00:08:44.258 --> 00:08:50.958 which is important as well, but it's usually designed. 00:08:51.138 --> 00:08:55.538 It is something, well, there are BPMN 2.0 models and all that. 00:08:56.158 --> 00:09:01.018 When it comes to data, we actually can take the data from the data source. 00:09:01.158 --> 00:09:02.038 It's actually available. 00:09:02.278 --> 00:09:06.398 It's not a design question at that point. It's actually just like taking the 00:09:06.398 --> 00:09:09.598 reality and mapping it into some sort of model. 00:09:11.258 --> 00:09:16.198 And if you're doing that, and if everyone would do that, then you are starting at the bottom. 00:09:17.258 --> 00:09:22.118 And if you're having now all the details, it's from a technical point of view, 00:09:22.198 --> 00:09:24.758 it's rather simple then to aggregate the information, 00:09:25.058 --> 00:09:31.298 and let's say you have a system containing 10 objects and each object has 10 00:09:31.298 --> 00:09:36.118 attributes, and that information is being shared with a different system and 00:09:36.118 --> 00:09:38.638 going to some other objects and attributes, 00:09:39.138 --> 00:09:45.338 then you can simply state, well, there is information flowing from system A to system B. 00:09:45.678 --> 00:09:49.598 It's something which is technically rather trivial to actually, 00:09:49.598 --> 00:09:53.238 well, get as an output. And that's kind of like what we did. 00:09:53.418 --> 00:09:58.158 We said, okay, make it simple. And if you start from the lowest level of detail, 00:09:58.438 --> 00:10:03.138 then you can aggregate the information to whatever you like, right? 00:10:03.638 --> 00:10:07.138 That is the magic behind the bottom-up approach. 00:10:08.498 --> 00:10:14.658 So let's go a little bit into implementation and start to understand how this normally looks like. 00:10:14.658 --> 00:10:21.718 Because I would assume you need at least one point where you actually connect 00:10:21.718 --> 00:10:27.158 to the system and get some access to all the data flows, 00:10:27.158 --> 00:10:29.718 and then you do an automated mapping. 00:10:29.938 --> 00:10:35.078 Is this something that happens, and how long does your whole process take? 00:10:36.760 --> 00:10:41.640 Fair question, and quite honestly, that is one of the most asked questions when 00:10:41.640 --> 00:10:43.420 we are talking to customers. 00:10:45.380 --> 00:10:51.700 Let's put it this way. We believe that a tool in itself is not worth anything, right? 00:10:51.820 --> 00:10:54.400 So you need to have the right methodology behind it. Otherwise, 00:10:54.640 --> 00:10:56.520 you are just about the fool with the tool, right? 00:10:59.140 --> 00:11:02.440 And to actually get to a proper information. 00:11:02.440 --> 00:11:06.980 So everyone has still this idea of, let's say, 00:11:08.000 --> 00:11:12.180 I want to automatically fetch information and send it somewhere, 00:11:12.260 --> 00:11:17.380 which translates for me into, oh, well, I want to give up the responsibility 00:11:17.380 --> 00:11:22.860 for my data quality and push it to some sort of API, to some sort of like automatism. 00:11:23.400 --> 00:11:27.740 And that is something which is contradicting to actually managing something. 00:11:27.740 --> 00:11:37.420 So, yes, there are possibilities to upload information like the data structure in that sense. 00:11:38.220 --> 00:11:43.360 We have focused actually a lot of our development just on that particular part. 00:11:43.900 --> 00:11:51.400 Nonetheless, it is part of the methodology to have someone who is actually responsible 00:11:51.400 --> 00:11:55.920 for the data architecture for one particular system and even interface. 00:11:56.180 --> 00:12:00.120 Everyone should have actually irresponsible person attached to it. 00:12:00.380 --> 00:12:05.300 It sounds weird, I know, because it's kind of like, well, you would expect that 00:12:05.300 --> 00:12:07.380 to happen, but reality is out there. 00:12:09.000 --> 00:12:12.340 Let's say there is a system, oh, we have just another one, okay, 00:12:12.600 --> 00:12:16.580 you already have two, now you have three, go, right? 00:12:16.760 --> 00:12:22.440 So that's the sort of responsibility we see out there in the market, 00:12:22.440 --> 00:12:28.880 because quite honestly, it is nearly impossible for a company of a certain, let's say, 00:12:29.040 --> 00:12:33.180 mid-size to have a dedicated person for each individual system. 00:12:33.420 --> 00:12:36.220 Nonetheless, we want to make it easy. 00:12:38.363 --> 00:12:42.703 And there are different ways on actually getting there. The simple path or the 00:12:42.703 --> 00:12:48.083 easy path is you just start with a couple of systems. 00:12:48.083 --> 00:12:52.343 You are just taking the information you know of and you are just like putting 00:12:52.343 --> 00:12:55.723 it in and you have a responsible person behind it. 00:12:55.843 --> 00:13:02.183 So the implementation journey for that company starts essentially with two workshops as easy as that. 00:13:02.323 --> 00:13:05.503 First one, we explain how it works. 00:13:05.703 --> 00:13:11.303 And the second one is we are discussing how the process, the change process 00:13:11.303 --> 00:13:16.163 actually works, because that is the most important part to keep the whole thing 00:13:16.163 --> 00:13:18.223 alive. Otherwise, you're just getting a snapshot. 00:13:18.563 --> 00:13:25.623 So it needs work. It needs, well, taking responsibilities up on your desk and 00:13:25.623 --> 00:13:28.483 actually managing it from that moment forward. 00:13:28.483 --> 00:13:33.583 But the gains you're potentially getting out of that are by far outweighed that. 00:13:33.783 --> 00:13:38.343 We may add a little bit about the data quality, why this is important, 00:13:38.363 --> 00:13:43.523 because you can not have any good decisions without good data quality. 00:13:43.683 --> 00:13:48.663 For example, what comes to mind is especially if you don't have like the real 00:13:48.663 --> 00:13:54.443 structure and real data properly maintained in your system, 00:13:54.523 --> 00:13:59.423 for example, You cannot have any financial derivatives based on that because 00:13:59.423 --> 00:14:01.463 there is like a big danger in that. 00:14:01.583 --> 00:14:08.503 And that basically works for a lot of other industries, a lot of other tools 00:14:08.503 --> 00:14:11.003 there as well, especially concerning 00:14:11.003 --> 00:14:14.243 pricing, especially concerning compliance and so on and so forth. 00:14:14.503 --> 00:14:18.863 And even pointing out the first point you mentioned in your introduction, 00:14:19.223 --> 00:14:28.143 everyone wants to use AI lately, right? That's like the new black, right? And 00:14:29.604 --> 00:14:34.284 You cannot use AI if you have proper data, because usually AI is, 00:14:34.364 --> 00:14:36.784 well, supposed to train on data. 00:14:37.264 --> 00:14:41.524 So if you are not aware on your data quality and you don't know where it's coming 00:14:41.524 --> 00:14:46.524 from, well, how do you expect your AI or how can you even trust your AI model 00:14:46.524 --> 00:14:48.764 or your data model, which is coming out of that? 00:14:49.984 --> 00:14:56.504 For me, there is a huge risk that, well, numbers are sort of like proving that 00:14:56.504 --> 00:14:59.424 it works, but do you know how long it will work? 00:14:59.604 --> 00:15:02.144 What if something changes? 00:15:02.444 --> 00:15:06.844 What if you need to train it on a different parameter? Where's the parameter coming from? 00:15:12.724 --> 00:15:19.004 But getting back to the implementation journey, I was just focusing on the easy path. 00:15:19.224 --> 00:15:21.104 So let's start simple. 00:15:21.424 --> 00:15:25.424 Of course, there's another way that you can actually go in and 00:15:26.744 --> 00:15:33.584 use some sort of consulting partner who is then dumping everything into the 00:15:33.584 --> 00:15:37.924 Coderflow environment and background to helping you setting up every tiny little bit. 00:15:38.284 --> 00:15:41.244 But overall, the whole process is, 00:15:41.444 --> 00:15:48.024 or the tools we are providing, it should not take longer than 12 and let's be 00:15:48.024 --> 00:15:53.544 generous, like 24 weeks because otherwise the data is outdated again. 00:15:53.844 --> 00:15:59.104 That's like what the majority of frameworks are actually suffering from because they are starting. 00:15:59.344 --> 00:16:03.844 And actually, we spoke to customers who are starting with like traditional tools 00:16:03.844 --> 00:16:05.304 in the data architecture environment. 00:16:05.424 --> 00:16:09.144 They start looking at documenting it. 00:16:09.284 --> 00:16:11.364 And in the end, it takes like two years. 00:16:11.624 --> 00:16:15.864 And then they have a picture, which is two years old. I mean, how useful is that? 00:16:16.704 --> 00:16:21.084 It's simply, well, not going to fly. That's very simple. 00:16:22.852 --> 00:16:26.732 And we are trying to change that. So that's exactly where we are really putting 00:16:26.732 --> 00:16:32.752 a lot of effort in and to make it as easy and pragmatic and simple as possible 00:16:32.752 --> 00:16:35.732 to get to a starting point. 00:16:36.452 --> 00:16:39.872 And from that starting point, and that is, well, allow me to just point that 00:16:39.872 --> 00:16:43.132 out, we are not trying to document anything. 00:16:43.332 --> 00:16:47.512 It is not supposed to be a documentation or tool in that sense. 00:16:47.512 --> 00:16:49.272 It's supposed to be a design tool. 00:16:49.412 --> 00:16:55.772 And I think that is one of the the major changes towards other methodologies, 00:16:55.772 --> 00:17:02.532 because we believe that it should start inside of a design process and not ending 00:17:02.532 --> 00:17:05.552 in a documentation process to actually gain control of it. 00:17:07.172 --> 00:17:15.732 You focus on a certain type called SMEs, or in German, KAMUs. 00:17:15.732 --> 00:17:19.352 There are more than three million smaller medium enterprises out there. 00:17:19.352 --> 00:17:31.332 I was wondering, how do you cater to the specific needs of this target group? Or why? 00:17:32.552 --> 00:17:41.052 Why? In general, data architecture in itself is usually part of something which 00:17:41.052 --> 00:17:43.812 is called enterprise architecture. 00:17:44.172 --> 00:17:50.012 It's a part of that and that part is, let's say, very complex and it is thought 00:17:50.012 --> 00:17:53.692 of, let's say, only for the enterprise companies. 00:17:54.852 --> 00:17:59.812 But enterprise companies is, well, maybe 25 percent. I don't know the exact 00:17:59.812 --> 00:18:02.512 number of the overall global industry. 00:18:04.011 --> 00:18:09.351 But the challenges of having multiple systems, and again, the numbers of 100 00:18:09.351 --> 00:18:12.571 plus systems is an average over all industries. 00:18:13.131 --> 00:18:16.331 So it's true for the midsize companies as well. 00:18:16.631 --> 00:18:21.811 So it is actually a problem which is not reserved for enterprise companies. 00:18:22.011 --> 00:18:23.711 Actually, everyone has the problem. 00:18:24.051 --> 00:18:29.771 So it was time to actually provide a solution for everyone as well and not only 00:18:29.771 --> 00:18:31.171 the enterprise companies. 00:18:31.891 --> 00:18:37.431 So for that reason, we were focusing on like, okay, let's do it in a pragmatic way. 00:18:37.631 --> 00:18:43.751 Let's really try to, well, tear down the boundary of, well, you need to invest 00:18:43.751 --> 00:18:48.751 multiple millions to make it fly and wait for multiple years before you can 00:18:48.751 --> 00:18:49.991 actually start using it. 00:18:49.991 --> 00:18:53.471 So, for that reason, we really try 00:18:53.471 --> 00:19:00.091 to come up with a way of working which is doable or affordable in terms of effort 00:19:00.091 --> 00:19:06.291 for everyone and not just like companies who can create a different department 00:19:06.291 --> 00:19:11.431 just focusing on that particular element of the design process. 00:19:11.691 --> 00:19:16.931 Does that make sense? It does. We've been already talking about change management 00:19:16.931 --> 00:19:20.291 because change management is very important, 00:19:20.311 --> 00:19:26.731 especially if you do have new systems, because if you ever try to remove one system, 00:19:26.871 --> 00:19:31.271 just unplug it and plug the other one in, that may work in a small network. 00:19:31.271 --> 00:19:37.131 But if you do have more than 20 employees, it will usually not work, 00:19:37.251 --> 00:19:41.371 or at least as well as one would like to have it. 00:19:41.371 --> 00:19:46.651 So, we need to do some change management and how does Kotoflow facilitate the 00:19:46.651 --> 00:19:50.331 effective change management within the IT systems? 00:19:52.611 --> 00:19:57.651 Good, very good question, actually. I think that's like the biggest differentiator 00:19:57.651 --> 00:20:03.151 between our solution and, well, let's see, other approaches out there in the market. 00:20:03.511 --> 00:20:06.831 So, here as well, pragmatism first. 00:20:07.551 --> 00:20:13.371 There is no need of a complex solution for a complex problem, right? 00:20:13.511 --> 00:20:16.171 So you need to come up with a simple way of solving something. 00:20:17.111 --> 00:20:23.231 And here is something, well, which we did not invent, but simply reused. 00:20:23.931 --> 00:20:29.171 Any software development company is so used to actually use code repositories. 00:20:29.471 --> 00:20:36.071 Essentially, data and its architecture in that sense is something like a code file. 00:20:36.071 --> 00:20:42.711 Like it is a structured way of describing how your data looks like and how it's 00:20:42.711 --> 00:20:44.771 actually built up inside of a model. 00:20:45.371 --> 00:20:50.931 So you can use that and use versioning behind that, right? So that's number one. 00:20:51.171 --> 00:20:56.871 So if you are doing versioning and you can ask anyone who has ever done like 00:20:56.871 --> 00:21:02.611 some sort of like, let's say, multiple people trying to contribute to a software project. 00:21:03.714 --> 00:21:07.814 You want to have something what is called a pull request. You want to have someone 00:21:07.814 --> 00:21:12.954 being the quality gate or the gatekeeper for anything which is going to move 00:21:12.954 --> 00:21:14.574 into that code repository. 00:21:15.074 --> 00:21:16.694 We simply reuse that. 00:21:17.394 --> 00:21:23.154 Whenever you are trying to come up with a new release, and the release for us 00:21:23.154 --> 00:21:26.434 means that you have changes inside of your data architecture, 00:21:26.854 --> 00:21:30.994 the system is going to follow up and trying to find out, okay, 00:21:31.114 --> 00:21:34.394 where is that data being integrated to? Where is it being shared? 00:21:34.614 --> 00:21:39.154 So who do we need to ask for approval if you may do that or not? 00:21:40.494 --> 00:21:45.734 That's literally what I have not seen in the market so far, because this is 00:21:45.734 --> 00:21:51.154 really implying that you are asking upfront before you're doing a change. 00:21:51.354 --> 00:21:55.414 And if you're thinking a little bit ahead of you don't need to necessarily do 00:21:55.414 --> 00:21:58.994 that at the very end, what usually happens, like after testing, 00:21:58.994 --> 00:22:04.794 You can actually start asking that particular question in that tool in the design phase. 00:22:05.094 --> 00:22:11.794 So you know actually what is coming up. And you can inform the people who should 00:22:11.794 --> 00:22:13.674 actually react upon that, right? 00:22:13.754 --> 00:22:18.254 If you're changing your field in a system, that might actually affect an interface. 00:22:18.254 --> 00:22:21.634 And that interface might affect another system and so on and so on. 00:22:21.654 --> 00:22:26.674 And it might affect the process of how somebody does his or her work. 00:22:27.254 --> 00:22:34.274 Correct. Correct. So, and that's like the beauty of it because we would, well, 00:22:34.554 --> 00:22:40.194 suggest to start with that instead of waiting for everything to be done and 00:22:40.194 --> 00:22:43.374 then starting testing and like, oh, well, it fails. Why? 00:22:43.574 --> 00:22:48.114 Yeah, because there is not, well, this field is now not supported anymore in 00:22:48.114 --> 00:22:51.474 our interface because there's a field length of 10 and we have now 12. 00:22:51.754 --> 00:22:56.334 I don't know, right? Just coming up with something. But that's essentially, 00:22:56.614 --> 00:22:59.694 now you can actually say, well, okay, I want to change it to 12. 00:23:00.434 --> 00:23:05.714 Who do I need to actually ask? And the system will figure out the path of that 00:23:05.714 --> 00:23:08.354 particular element throughout your whole data landscape. 00:23:08.754 --> 00:23:12.794 And we'll create a task for everyone. And asking the question, 00:23:12.954 --> 00:23:16.434 okay, well, are you feeling okay with that change? 00:23:16.474 --> 00:23:18.514 Or do you need to react upon that? 00:23:18.634 --> 00:23:24.094 And then we are basically orchestrating that communication between the different system owners. 00:23:24.594 --> 00:23:30.094 And sort of like pushing out the change before it actually happened. 00:23:31.894 --> 00:23:38.274 That sounds pretty interesting. We will be back with more stories about you 00:23:38.274 --> 00:23:40.134 and Codaflow after a short ad break. 00:23:45.054 --> 00:23:50.774 Hey, guys. Welcome back to my interview with Stefan Opitz of Codaflow. 00:23:51.954 --> 00:23:55.394 We will be now talking a little bit about real-time collaboration. 00:23:55.934 --> 00:24:02.574 In what way does Code of Flow enable the real-time collaboration among the stakeholders in the company? 00:24:05.434 --> 00:24:11.714 That's actually a very, let's say, critical element of the whole solution. 00:24:12.174 --> 00:24:17.414 So, again, coming back to our past, so we have been doing a lot of integration 00:24:17.414 --> 00:24:19.534 projects between different systems. 00:24:20.094 --> 00:24:26.274 I would say 10 out of 10 start with a sentence, let's open up an Excel spreadsheet 00:24:26.274 --> 00:24:31.014 and let's combine forces and mapping fields and objects. 00:24:32.034 --> 00:24:35.894 Well, in some cases, it might not be Excel, it might be Google Spreadsheet. 00:24:36.034 --> 00:24:39.914 It doesn't matter, right? But in the end, it's just a spreadsheet where everyone 00:24:39.914 --> 00:24:42.014 is trying to collaborate on. 00:24:43.354 --> 00:24:47.414 Main drawback, you don't have any data model information at that point. 00:24:47.414 --> 00:24:50.114 You just see, well, attributes. 00:24:50.334 --> 00:24:52.934 It doesn't tell you anything about cardinality or anything. 00:24:53.434 --> 00:24:56.574 The other point is, oh, I have seen it. 00:24:56.934 --> 00:25:00.794 Oh, let's filter it. Oh, let's resort it. Oh, unfortunately, 00:25:00.874 --> 00:25:06.054 I did not have all the different columns in my working area. 00:25:06.274 --> 00:25:07.834 And suddenly, the work is gone. 00:25:08.454 --> 00:25:10.934 So it has happened to me multiple times. 00:25:12.414 --> 00:25:19.134 So we said, okay, let's stop that. Let's actually put some sort of model behind it. 00:25:19.234 --> 00:25:25.514 So meaning that we created purposely our solution as a web solution where everyone 00:25:25.514 --> 00:25:29.654 can collaborate in, like in a Miro board, for instance. So, whatever you're 00:25:29.654 --> 00:25:32.334 doing, the other person sees at that very moment. 00:25:32.954 --> 00:25:37.974 And we have a split-screen approach, meaning that you can have, 00:25:38.114 --> 00:25:40.374 on one hand, your table with your attributes. 00:25:40.374 --> 00:25:45.914 On the other hand, you can actually see the data model or even the integration in itself. 00:25:45.914 --> 00:25:50.674 And you just, like, basically connect the dots as, well, working, 00:25:50.934 --> 00:25:54.154 talking to the other person who is responsible for the other part. 00:25:54.154 --> 00:25:58.534 So it's basically if you're a part of the left side, you're connecting the middle 00:25:58.534 --> 00:26:01.334 part and the other part is connecting the middle part to their part. 00:26:02.134 --> 00:26:07.754 And this is like how we envisioned how we would like to work when we talk to 00:26:07.754 --> 00:26:12.114 someone, because usually we are in like the left part of that system. 00:26:12.334 --> 00:26:15.494 We are providing information and we would like to simply say, 00:26:15.574 --> 00:26:17.974 OK, well, what do you need? This is what we have. 00:26:18.154 --> 00:26:22.594 See here, putting it in and saying, okay, let's now actually talk about how 00:26:22.594 --> 00:26:24.214 this is actually being connected. 00:26:24.594 --> 00:26:27.594 So that's kind of like our approach. 00:26:27.774 --> 00:26:33.734 So we purposely didn't want to create another spreadsheet solution. 00:26:33.734 --> 00:26:41.154 We wanted to combine a system model, including the, let's say, 00:26:41.694 --> 00:26:47.534 Excel-like experience and background, plus putting some permissions on top of 00:26:47.534 --> 00:26:53.254 that, because we felt like that is something which is desperately needed in that regard. 00:26:55.000 --> 00:27:00.020 I have a question in terms of understanding. You do this once and the system 00:27:00.020 --> 00:27:02.360 then automatically updates itself? 00:27:03.660 --> 00:27:11.500 It does not update itself by definition, but remember I said we have the design first approach. 00:27:11.780 --> 00:27:16.400 So if we would actually go for the system to update it by itself, 00:27:16.580 --> 00:27:20.820 like using some APIs or reading SQL tables and background and all that, 00:27:21.000 --> 00:27:23.960 that would actually be really difficult to 00:27:23.960 --> 00:27:27.040 handle because we want to actually react 00:27:27.040 --> 00:27:29.660 before the change happens so if we 00:27:29.660 --> 00:27:32.540 want to react up front then the approach is well 00:27:32.540 --> 00:27:35.920 we have the design first meaning that you are planning what 00:27:35.920 --> 00:27:40.500 you want to do before it actually happened so for that reason you are starting 00:27:40.500 --> 00:27:45.540 at that point and the second part is you have a versioning model behind it so 00:27:45.540 --> 00:27:50.420 if you're uploading something well to what version to what release is it already 00:27:50.420 --> 00:27:54.140 approved do we merge who is deciding on that right So, 00:27:54.300 --> 00:27:57.700 these are all the little elements which are, let's say, 00:27:58.480 --> 00:28:02.300 well, the consequence of having a proper change management behind that, 00:28:02.480 --> 00:28:08.500 but it allows you to really have an unknown quality of your data model, 00:28:08.500 --> 00:28:12.760 which has never been done before, because now you can actually trust the data, 00:28:13.020 --> 00:28:16.240 which is different from what we have seen so far. 00:28:16.540 --> 00:28:20.800 No one trusts documentation except their own, maybe. 00:28:22.772 --> 00:28:24.072 And maybe, really maybe. 00:28:24.532 --> 00:28:32.492 It does make sense. We've been talking about AI training. Data transparency is here a big topic. 00:28:32.752 --> 00:28:37.772 How do you enhance this data transparency and governance? Because that is really 00:28:37.772 --> 00:28:43.732 something you should first have nailed before you even start training in an I.O. and data. 00:28:44.172 --> 00:28:48.592 That's excellent. Well, actually, this is a perfect, well, next step because 00:28:48.592 --> 00:28:50.072 we we're just talking about it. 00:28:51.812 --> 00:28:56.892 If we are talking about data transparency, it means to have a versioning behind it. 00:28:56.952 --> 00:29:02.452 It means that you need to have a trust-worthy data source for that as well. 00:29:03.112 --> 00:29:08.012 Right now, the majority of companies, at least I have seen, well, 00:29:08.112 --> 00:29:13.332 at best they have some sort of like, well, data dump called Confluence or alike. 00:29:14.292 --> 00:29:20.672 Well, no pun intended here. It's just that someone is writing that because it 00:29:20.672 --> 00:29:26.452 has been the contract that you are providing some sort of technical documentation. 00:29:27.392 --> 00:29:32.312 So you're just writing it down, basically, well, dumping it somewhere. 00:29:32.312 --> 00:29:37.532 And I would even say the majority of these documents is, well, 00:29:37.952 --> 00:29:41.272 read by yourself and potentially one or two other people. 00:29:42.052 --> 00:29:47.052 And now you have different systems and you have different contributors and everyone 00:29:47.052 --> 00:29:49.392 is writing it in a little bit different way. 00:29:49.752 --> 00:29:56.312 In the end, you're getting, well, some sort of documentation or arguing about that. 00:29:56.492 --> 00:30:02.332 But if you want to create a big picture out of that, it's rather impossible. 00:30:02.332 --> 00:30:09.032 And that's why we are saying, okay, let's bring everything in one spot and have 00:30:09.032 --> 00:30:12.792 a proper process behind it, have proper responsibilities behind it. 00:30:12.892 --> 00:30:19.152 And then suddenly you have a transparent data model and a data model which you 00:30:19.152 --> 00:30:23.452 actually can rely on, which you can trust on, because you have put the proper 00:30:23.452 --> 00:30:27.492 processes in place to support that. 00:30:27.652 --> 00:30:31.252 But that only works if everyone is contributing, right? Otherwise, 00:30:31.612 --> 00:30:39.232 you again will end up in a situation where you don't really trust the data anymore. And that's the part. 00:30:42.776 --> 00:30:48.816 Could you talk about training AI? Could you also use your tool to investigate 00:30:48.816 --> 00:30:55.576 if something is going completely off the charts with the AI if it's not inherent in the model itself? 00:30:55.916 --> 00:31:00.616 Well, we don't touch the data in itself. So we don't know what the data is because 00:31:00.616 --> 00:31:02.276 we purposely designed our... 00:31:02.276 --> 00:31:07.496 I was referring that some AI models are known to go off the charts. 00:31:07.836 --> 00:31:13.576 They are unstable, and some of them are performing good to really good, 00:31:13.716 --> 00:31:18.136 but they still can be issues. 00:31:18.436 --> 00:31:22.876 And if you could use your tool to investigate if one of the issues may be in 00:31:22.876 --> 00:31:24.136 the data that you've had to it. 00:31:24.136 --> 00:31:32.156 At least we can, well, if we have that data model inside of our landscape, 00:31:32.316 --> 00:31:38.456 basically, at least we have a very clear understanding on where information is coming from, right? 00:31:38.596 --> 00:31:43.256 So we can definitely plot the path of all the elements which are going in there. 00:31:43.676 --> 00:31:48.976 So if it is being fed by, I don't know, let's say you have customer data and 00:31:48.976 --> 00:31:52.476 you have order data and both of them are being combined. 00:31:52.476 --> 00:31:58.396 But the customer data is coming from an online shop and the order data is coming from an ERP system, 00:31:59.056 --> 00:32:03.956 then there might be an inconsistency between these two because there might be 00:32:03.956 --> 00:32:08.616 a mix-up of data sets and not the right data quality. I don't know. 00:32:08.876 --> 00:32:14.276 So at least you know where to look at. So we don't know what data is being exchanged, 00:32:14.276 --> 00:32:19.256 but we know the data types or the data sets in that in that sense. 00:32:19.636 --> 00:32:25.696 So I would say, yes, it is definitely a good starting point for your investigation. 00:32:25.716 --> 00:32:31.036 We at least help you to identify the areas where you should look first. 00:32:31.936 --> 00:32:36.896