My Career in Data Season 4 Episode 12: Lulit Tesfaye, Joe Hilger, and Zach Wahl, Leaders at Enter...

[music] Hello and welcome. My name is Shannon Kemp and I'm the chief digital officer at data and this is my career [music] in data, a data university talks podcast dedicated to learning from those who have careers in data management. To understand how they got there and to talk with people who help make those careers a little bit easier. To keep up to date in the latest in data management education, go to dativersity.net/subscribe. Hello and welcome to my career in data, a podcast where we discuss with industry leaders and experts how they have built their careers. I'm your host Shannon Kemp and today we're talking to a group from Enterprise Knowledge. Today we are joined by Lulite Tesf, partner and VP of knowledge and data services, Joe Hilar, chief operating officer, and Zach Wall, president and CEO from Enterprise Knowledge. And normally, this is where a podcast host would share a short bio of the guests, but in this podcast, your bio is what we're here to talk about. Hello, everybody. >> Hello. >> Hi, Shannon. Thanks for having us on. >> Oh, I'm so excited. I love a group interview. Okay. So, uh the reason for having a group interview uh and the reason we brought you all together today is the three of you have co-authored a new book titled Bridging Knowledge Data and AI harnessing the semantic layer framework to drive intelligence. Now, before we get to the book and how it came about, um let me just ask you to introduce yourselves. So, um and introduce your company. So you all work for enterprise knowledge uh work for and have founded and so tell me for those of you who may not know uh what type of business is enterprise knowledge whoever wants to to share. >> Uh happy to to lead off. I'm I'm sure my colleagues will uh want to chime in with with some color as they want to do. Uh Enterprise knowledge we are the world's largest dedicated knowledge information data consultancy. We uh are in the business of connecting people to the information they need to do their job. And over the years uh that has turned from being a a very human ccentric pursuit a lot of information architecture taxonomy ontology to the current stage of semantics where we're really helping organizations to make their AI initiative successful to add context to as the book is called build bridges between their different sources of information different knowledge assets and their different forms and deliver trustworthy glassbox AI in ways that really add business value. Joe Ly, what did I miss there? >> I think you got it all. We, you know, simply put, we we do this for companies around the world, helping them make their data easier to find, work with, and and and actually now powering a ton of AI projects. >> Such a hot topic right now. [snorts] So, Zach, let's start with you. So you are president and CEO. Uh tell me what is it you do? What's your day-to-day look like? >> Yeah, I I I don't know that there's a specific day today. Uh I can tell you that typically uh I am focused more on long-term strategy and growth of the organization. Uh so there's a fair bit of marketing, business development, uh a view towards what's coming next in the industry. Uh and so in a way I in addition to CEO I wear the CMO hat from that perspective or the the CSO as in strategy not security god know. Uh and uh I also do a fair bit of uh work on the people side. So uh working alongside our HR department to really foster a community of collaboration, kindness as we call it to ensure that we are supporting each other and uh learning along the way. Uh that said, everything I just said, I would say Joe and Ly also do. Uh so for instance, Luly was the one who identified semantic layer as a really hot growing trend that we needed to be all over. We'll we'll say more about that as as the interview proceeds. >> Oh, I love it. And I'm not surprised at that revelation. I have worked with Alina V, so um I know she's on top of things. Um but let's u move to you Joe as the chief operating officer. What is it that you do? >> Oh, a lot a lot of different things. So I do security among other things. Uh not my favorite but but super important for our clients. contact reviews, all of operations, everything from finance and accounting through our our delivery process and our PMO. And then I've been working with the teams a lot on some of the demos and and reusable components that we're that we're giving to our clients so that they can be more effective faster. >> Very very nice. So um Lulit, I've worked with you quite a bit. I know you probably um uh I've known you for a few years working together and and I'm just now um getting the opportunity to meet Zach and Joe. I'm very very grateful for that. Um but tell me um as a VP of knowledge and data services. Same question. What is it you do and what's your day-to-day look like? >> Yeah, I I share the sentiment. No. Um there is no such thing as day-to-day. However, uh as a in this role, uh there are multiple hats, but primarily um successful delivery in everything that we do from strategy, design, and implementation. That's the core of our work, our integrity, why we're here. Uh and then uh in addition to that charting the path for how we grow our people from skills, expertise development, identifying the gaps that we have in you know how things and technology are involving but also what our clients are asking for and looking for and being able to to think two three steps ahead of our clients to be able to help. So charting but looking ahead uh thinking about uh how we can leverage our collective experience in light of emerging technologies staying a breast of that that's a big part of this uh invigorate into that in partnership with Zach and Joe marketing uh compliance uh all the things that we would have to have in place uh to support the large institutions that we work with. So that's a big part of my day. If I didn't have this virtual B board, you will see a lot of whiteboard behind me of all the solutioning and thinking that we do with my with like my team members. So I find fun uh and thrilling excitement every day cuz every problem is different uh every day. So that's in a nutshell um what I do a day in a life so to speak. >> I love it. Well, let's let's uh work the other way. So, uh, in terms of responses, so Lily, uh, how do you work with data in your day-to-day job? >> That's a tough question and I I'm going to take a little bit of a step back and define data a little bit because I know it means there are many different things to many people. Uh, and I think this is in our journey also. Um as as Zach called out earlier uh we started as a knowledge management company and uh a big part of that was that uh uh traditionally it's considered as tacet knowledge capture uh that that piece of these the people expertise connecting that piece shifting into information management as a big part of that. How do you translate that into these uh applications and machines? And over the especially over the last decade um to answer the organization's questions of finding and connecting them to their information, a big part of that lives in what traditionally is structured data. So when we talk about data or like we collectively call it knowledge assets uh we what we are doing on a day-to-day basis is connecting that those assets the knowledge the information uh and the data within them but also not just for humans today it's making that machine readable u so for machines as well. So the way we work with quote unquote data now is in the form of treating it as a knowledge asset uh just like everything that you have within your organization and that you can describe to humans as well as to machines. Uh that's kind of like a highle overview of that and then when you get into implementation there's the plumbing there's the engineering there's the modeling that my team uh works on that I guide and uh also architecture as well. Uh so that's a a core part of how we interact with and work with data and knowledge assets. >> Yeah. Is is there data or is there how are you staying on top of on of that of what's coming and what's hot and what's not? >> Yeah. Uh well a lot of it is also partially where we first met you and I uh we attend your conferences. We are embedded on uh a lot of the industry events. We speak at conferences uh as well as a big part of this. So we have a lot of team members I know you've met uh that attend these industry events, industry conferences. We host a conference ourselves on semantic layer symposium. Uh so we have uh we are out there uh but also because we work across many different industries we are able to cross-pollinate lessons learned and case studies and the bruises and uh all of that to bear for our organ organizations. Zach or Joe if you want to add anything else there. >> I would we're in a neat position. Uh the number one way that that we get new clients and win new work is that they reach out to us. They've read our knowledge base. They've seen us speak at these conference conferences that Luly mentioned. And so we have a lot of people we don't know reaching out to us. And I think one of the the greatest data points is what they're asking for, the words they're using, uh what's in the RFP, what are the deliverables, the problems that they're having in the words that they're uh using to describe them. It's incredibly insightful. And as we every year publish our various trends articles, that's one of the greatest inputs for it is frankly what's top of mind for the cos and CEOs around the world. >> You know, and I think I would also add uh we've invested a lot in collaboration and community inside of EK. So Shannon, we tell our clients, you get you get all of EK when you hire any of us. And it's really true. Um the three of us just left a knowledge share companywide to talk about something new or a skill etc that we're doing. We've held that since the company began. Uh we have sessions all all along communities of practice where people are coming up with new ideas. Um and that that lets us bring new ideas to our clients and really encourages the right people to join EK. The ones we get are very interested in being cutting edge and and wanting to do neat stuff. >> Nice. Well, Jill, let's move to you. So, how do you work with data in your day-to-day job? >> Um, >> COO. Yeah. >> So, I leave out client data because that's what they're doing. But I I you know, data is an issue really an issue for me. Uh, we've got to make sure we have it. It's properly protected. Every agreement I sign says that we are going to be very careful and cautious with our clients data. So we've we've had to build processes around how we collect data and then how we get rid of data when we're done with it. Um so I'm that that is one part of my life that that is uh you know important and I'm attuned to. And then you know beyond that uh we've [clears throat] always wanted to act bigger and more mature than we were so that we could grow into ourselves. So, we've had data about sales processes um in in HubSpot for for years now. Uh we have project evaluation data that's been collected week over week. Um Lillly and I were just looking at our KPIs across projects so we could find ways to figure out if we were not meeting our clients needs, we wanted to jump in more quickly and make sure we fixed it before they came to us. And so we we we spend a lot of time trying to use data to help guide us in our decision-m process. >> Very nice. And Zach, same question to you. >> Yeah, I think Joe and Luly uh covered it really well. The one that I would add is uh we've always had a growth mentality and so uh decisions around hiring uh have always been really datadriven as well as decisions about uh marketing uh moving into new markets and launching new products. All of that uh uh leverages uh a number of different inputs as well as of course some some good luck and gut to go along with it which never hurts. Absolutely. All right. Well, that is nice. Um, so tell me then, uh, what made you all decide to, you know, let's write a book together? >> Yeah, it's Lit's fault. Definitely. [laughter] We were, uh, it was uh, late 2023. I already mentioned that Lite was the one who surfaced. The the concept of the semantic layer was something we'd been doing for years. I mean from EK's very first day we were doing taxonomy design. Soon after we were doing ontology design we were one of the first into the knowledge graph market. We've been focusing on on quality and metadata around knowledge assets really for 13 years now. So the component parts had always been there. They are and have always been our core services. But Lulit was the one from the very specific vantage point in which she sits who came to Joe and I and said this is going to be the thing that everybody's talking about in 2 years. I mean that's a direct quote. So uh you should probably be going to her for lottery tickets and and stock tips at this point. Uh so uh in uh early uh 2024 uh the three of us as well as Sarah Nash a practice leader here at EK uh went and did a a weekendl long offsite to talk about how we would guide this conversation. Uh shortly thereafter we started doing a lot of blogging on the topic. We launched the semantic layer symposium, our annual conference in Europe on the topic and we had a whole Trello board of of different things from from marketing from hiring to internal education that that we would work on and you can actually chart the spike on Google trends and everything else as uh the term grew and grew and grew. Now, back then, we had no idea exactly how much of an impact all of that would have on AI and how important the AI conversation would be today. So, there again was a little bit of luck in the the thinking around this. But one of the things on the trellboard was let's write a book. And it was a little bit of a slow start. Uh it was certainly a bit of a slog as as we we went through it, but that was the impetus of it. a uh a weekend in Orange, Virginia, where we uh plotted out a multi-year strategy around semantic layers. >> Oh, I love it. So, tell me a little bit about the process and uh um tell me a little bit more about the book. What what's your favorite part of the uh of the book that everybody should know about? >> I'll start there. I'm sure we have uh different perspectives on this. Um I think you know the the biggest point um semantics and semantic web have been around I think we just celebrated this 25th year anniversary actually this year and to Zach's point this is not something new um and the what makes this exciting and why now like the biggest driver being AI is that um a lot of uh traditional data uh side of the the structured data. Uh there is also a concept of the semantic layer which we call the metrics layer which is very different from what we're talking about. I think that's the distinction that I would like to articulate. When we talk about a semantic layer, we're talking about the things that refer to meaning and not the physical data. So metadata, taxonomies, ontologies, graphs, uh the components that Zach talked about, business glossery fits into that as well. So the most exciting part of this is in a way to be able to create clarity especially on the market because uh there has been uh I empathize with a lot of leaders right now uh it is very hard to make a decision about solutions technology uh just the vendor market is very vast and that's exciting in its own right but if you are an executive if you're a co or a CEO like an AI lead leader it is very hard to make this decision. So what really excited me about writing this book is we have been living the scars and the gray hair maybe you cannot see through the camera right now uh over the last few years and to be able to capture that all to be able to reflect back to all of that and capture that in real world case studies but also don't do what we did in areas where early days where we we screwed up for instance right like or learned a big lesson so being able to capture all of that it was just a a journey of reflection but also an opportunity to cl create clarity and uh provide reason into what's going on in the space from just our experience. >> Now uh one thing to add to this Shannon we we've got a whole section on case studies and so many of the people that author these books talk about technologies but haven't always done them. It was really important to us to be able to say what you're reading is real and and people have done it and it's worked. And I I I really think that's important for someone to have the confidence to do stuff like this. [music] Whether you're leading a data program or building your career from the ground up, the data [music] training center meets you where you are and helps you get where you're going. Explore expert-led courses, industrybacked [music] certifications, and flexible subscriptions designed for realworld application at every level. Get practical insights you can use today. Start learning at training.dativersity.net. [music] All right. Well, let's talk a little bit then about your backgrounds and how you got to be where you are today. Um, one of my favorite questions of these interviews is, you know, when you were very young, say 6 years old, was this your dream? Did you think I'm going to found or I'm going to work for, you know, a knowledge management company or what was the dream at at six? Joe, let's start with you this time. >> Okay. Well, little before that it was probably firemen, but I think by six or seven it was going to be Mark Price playing in the NBA. At 5'9 and a half, 510 that probably wasn't real. So somewhere along the line I I I switched off to maybe something that that was a better fit for for me and uh started in consulting from day one out of college and have been doing it ever since. >> Wow. always always in uh the data field or >> no that's been a journey um >> started at Coopers and Library >> uh >> uh which I guess is now PWC. >> Uhhuh. >> And I you know early on I was doing data um for banking. Um but then moved into gosh in the late 90s uh content management when that was a hot thing and enterprise search and then did a lot of work with uh if you remember Mark logic and kind of the the XMLbased data work and >> you know just kind of been into into graphs etc. It's it's been kind of following what made sense to me. >> Yeah. I I love the fireman to basketball player to consultant. What so when what was the study what did was your focus of study as you started getting older? What did you form a passion around? >> So my my I was a finance and and basically computer science major. So probably a little bit what I do now. Um >> yeah, makes sense. >> I coded a little bit when I first started. It's been a long time. >> Probably I'm not doing that anymore for everyone. Yeah, I I'm with you. [laughter] It's not It's not my thing. I've tried it, but uh and grateful for anyone who who's who loves it. Uh Lily, tell me, what did you want to be when you were 6 years old? So, yeah, I have like the most I think the zigzag path down to this to where we this room. Uh I wanted to be a lawyer and I became one actually and then uh realized that a a couple of years in um maybe not something that I want to do litigating for for a lifetime. So to took a small pivot, shifted to an MBA and uh majored in uh finance as well as uh process program management and I ended up working in the financial services space, mutual fund investments management. That's when I started dealing with data and applications uh as a core part of my work. And from there uh I went into financial regulations which kind of brought the legal experience with the data the financial industry kind of came together and that's where I was more working on building applications web applications for uh data and regulatory enforcements and um that's when I met Zach and Joe. Uh that was that is now 10 years ago and uh I I joined Enterprise knowledge. I think I was employee number nine. I don't know. Uh we were very small back then and um and the rest is history. Here we are. >> Oh yeah. So Zach, same question. Where where did you want to start? Did you envision like I'm going to co-ound and with with Joe this company? >> Yes. I I weirdly uh I I I was probably the closest here. I when I was a kid, I I grew up pretty humbly and so I wanted to be a businessman. I wanted a briefcase and a suit and I didn't know actually what that would entail on a day-to-day basis. But my uh my parents the last time they moved, they dug out a picture I had drawn uh in my pre-teens and it was of my future uh office building. And I I can say that uh with the exception of the fact that it had a slide that went around the outside of the building, it's it was pretty spot-on across the board. So yeah, I'm kind of doing exactly what I dreamed of doing in life, which is amazing. >> I love that. So uh where did you start, Zach, in your career? I mean, where, uh what was your first job? >> Uh consultant. I've been doing this my entire career. I uh my degrees are in environmental science and political science. I got a job in consulting uh right after college and uh initially I was doing environmental consulting found that I didn't want to uh travel around the country uh sleeping in CD motel while doing uh soil samples of gas stations. Uh but this was 98 and so I had a really cool CEO at the time and I went to him and I said I would like to see what else I could do. I don't want to leave. and he was just in the process of starting a a web design practice within the company and the rest as they say is history. And then the fact that I couldn't code and didn't want to learn how. So I found the role for myself which was to be the translator between the business and the the technology. I've been doing that ever since. Spent most of my career uh in the the the first uh consultative days doing taxonomy design. So I'm a taxonomist by trade and obviously expanded that into kind of a broader knowledge of of different knowledge management techniques and information architecture and now semantics. >> Nice. So um I always like to ask some of entrepreneurs you know what made you want to start your own company you know why did you guys co-found uh enterprise knowledge? Yeah. So, it it had truly been the thing I'd always wanted to do. I uh I'm a very optimistic person. So, uh when I buy a lottery ticket or when I bought a lottery ticket in my 20s, I would always be disappointed when I didn't win. Like, I actually I know the odds and I still was like, "Oh, shoot. I really thought this was the one." But I would always dream, as I imagine pretty much everybody else does, of you know, you buy that ticket, what would I do if I won? And what I always dreamed I would do was start a consulting company. And so, uh, again, I I I feel incredibly grateful. I feel like I'm I'm living my dream. I won the lottery, so to speak. Uh, but it was it was what I always wanted to do. It took meeting Joe and having my previous company uh be acquired by a VC and me getting fired uh to actually start EK. So the the origin story is that I was unceremoniously dumped from uh my previous company, one that no longer exists. And uh Joe, who I had known for years is a little bit of a a competitor uh and a little bit of a collegial uh partner uh called me uh about 2 days in to unemployment and said, "What happened?" You know, everybody everybody gets that call. And uh so he asked me at that point if uh I'd be interested in going into business with him and and after a little heming and hawing, it ended up being a a pretty easy yes. >> Yeah. And Joe, what made you make that call? >> You know, uh I was I I ran the branch office of a of a consultancy and they were doing fine. We were actually the most profitable office. I I asked the founders for equity and they said, "Sure." Um, but they said, "It's still our company. We're going to make all the decisions." And I I remember looking at uh good friend of mine who had brought in to help me run the office and I said, "Neils, it's uh I I want to I want to drive something." Mhm. >> And I said, "So, it's probably time for a change. You'll take over the office." And I said, "You know, Zach knows everyone. I'll call him next week." That Monday, I look, wait, Zach's not at PPC anymore. What just happened? >> So, I had planned to actually call him two or three days before, so timing would have been worse, >> but >> Oh, is that was meant Yeah. And that's meant to be. And I love hearing the those kind of stories where you know, Zach, it was a hard time probably uh a panic moment and uh but uh it worked out right. >> I I love talking about it and and I will say that when I got canned, I had just this epic imposttor syndrome come washing down on me. I just terrible feeling of saying like, "Wow, you know, maybe I really didn't deserve that opportunity. maybe I shouldn't have been in that position. And it was it was really crushing. Uh there was there was a weekend of uh a fair amount of uh wine being raided from my collection uh before I decided to figure out what what came next. And and it was it was a hard uh few months as we first started out. And I share that story really freely because I think so many people in their careers are self-limiting. they're they're limited by their own imposttor syndrome. They're worried about taking the risk and ah it doesn't always work out but boy uh getting fired was the best thing that's ever happened to me professionally and um I'm I'm really proud to get to work with with these two wonderful people and then the the very te deep team of of of kind and smart people that we have built. Uh it's just it's like I I'll say it again. It's a dream come true. I will say I um everyone I have worked with from Enterprise Knowledge is exactly that. They're very kind. They're very knowledgeable. They're very professional. They're very easy to work with. Um in fact, you mentioned Sarah Nash earlier. Le recommended her to me to um be a moderator for uh a panel for our online conferences. And now she's our moderator for every keynote panel because she's so amazing. >> She is. [laughter] She she is amazing. >> Yeah, >> she is. Yeah. Yeah. Um All right. Well, so so tell me uh and D, I'll come back to you since you were just mentioning this. So is this was that your biggest lesson so far in your career or what has been your biggest lesson so far in your career? You know, I there are so many, but the the one that that I always like to talk about when someone asks that question is uh to to show up as yourself at work. Uh I actually before EK, I was a young manager. I was a young executive. And I think I I flubbed it. I think I was overly formal. I acted like the businessman I dreamed of being when I was six instead of being myself. and it was not wholly authentic and I don't think that's somebody that's easy to follow. And so coming into EK uh I had a lot to lose but in a way I also had very little to lose and Joe was such a natural uh human manager. He taught me a lot about uh how to show up at work and and how to to to be yourself. And so I I learned from him and and uh I think he's he's made me a better leader and and manager from from that uh being a little more vulnerable, a little bit less formal and uh just really showing up and being yourself in the office. >> A a great lesson and and Joe, since your name was just invoked there, you know, let's uh let's throw the question to you. You know, what has been your biggest lesson? think it's about always learning. Uh, you know, I talked about I started in consulting, but I did a bunch of things along the way and as I've watched EK grow, I mean, what what Zach and I started doesn't look a bit like this. And it's because uh we've been learning, everyone in the company's been learning, and we grow together. And and it's [clears throat] it's so easy to when something doesn't go right to step back and go, "Oh, I just learned something." As opposed to, "Wow, that was awful." Right? And and I I think just for me, if if you can keep that spirit of learning going as long as possible, it'll make things fun. It'll protect you and keep you up to date. Um and it it makes it easier for everyone to work together. >> Yeah. Yes. also a a very good lesson. Uh one I wish I had learned much easier earlier in my career. >> Wait, uh tell me what's been your biggest lesson so far in your career? Yeah, I um I would say uh I think my actually my career path is a testament uh to this journey uh which is um being able to take risks and open to learning and change um is a a big part of the lesson of why I am doing what I'm doing, why uh we are all in this room. And also a big part of that is um especially if you are ambitious and driven being kind to yourself where you know the six-year-old me did not know um first what lawyering is it was going to end up being but the second aspect of it is I mean all the tools like Facebook did not exist at that time the internet like you know all without aging myself the world changes and um with the 18-year-old self may have had different ideas for my myself now. So being able to consistently reassess and learn and as long as you're moving taking risks and moving on and I think that's a happy life. Um that's what what I've learned through this journey. M again another another nice lesson and part of why you know we started this podcast to show that uh careers in data management haven't come through a linear path necessarily unless you know you're an analyst or or uh maybe a data scientist but there's so many different ways and it is through that change that uh that people get into this into >> yeah and if I could add to that actually Shannon I think it in fact the more you don't have a a linear path, the better contributor you are uh to your team, right? And uh so staying curious and just being open about different ways of working uh is a big part of I think a big part of my uh my life and my journey, but also how we lead this organization and why, you know, I'm still a big part of this. >> We see this at DK, too. I mean, we we're really proud of uh recruiting folks in the beginning of their career and uh developing their consultative skills as well as their technical skills. And it's always made sense. I mean, the work we do is so cutting edge, it's not like anybody's going to learn it in a program anyways. So, we did the last time we checked, we we have people with 18 different uh majors and those Yeah, sure. Tons of data science and cops people, but philosophy, English, history, literature are really neat. >> Oh, yeah. >> Yeah. >> Yeah. That's I love that. I love hearing that. Yeah. I I mean I've met film producers who became uh data architects, you know, lots of lots of uh interesting career choices and paths and and it is from that again that change and not being afraid to change and and discover um your passion. [clears throat] >> So uh tell me I mean you all have been working with data for quite some time. you're building a career and company around it. You know what is you Lee Lee? You mentioned your definition earlier. You know, do you have a a corporate or just a general definition of data? >> Yeah. Uh I I think this is part of also like our our our journey together going through the different um parts of the organizations that we work with and I think there's a little bit of a lot of this is driven by what's happening in the technology world. Uh it has always been actually for the most part but I would say there's a slight change uh in how we think about data as a result of the advancement in technology. Uh and so this is why when I defined data earlier, I use I used the definition of a knowledge asset because it is beyond just the stuff you have in your tables and spreadsheets. Uh it it lives everywhere. Anywhere you can attach a metadata or a descriptive thing around to or label to is an asset. So we see um the traditional structured unstructured semistructured concept of data blurring and expanding to different aspects of these assets and different metadata. So think people think with the internet of things you're you have uh these different things coming in uh you have processes you have procedures all these inputs that um that are required to power uh well traditionally you would say your search solution uh but now I would say even AI is a big driver of that so that's how we significantly see this shift uh it's still catching on but we've been uh talking about this and talking about bridging. In fact, actually this is how we ended up in the semantic space is it makes no sense to have the data team sit here and the content team sit here and have the the the organization try to answer a question which needs both of them uh to to work together or break down the silos. So that's a that's how we're seeing the definition of data pivoting and the biggest I think lever of that now is the data team it cares about knowledge the traditional data team is shifting into knowledge because that is in the form of context right that is the the bedrock of making an AI successful AI successful or a failure which we've seen a lot of the the latter >> yeah I agree Agreed. Uh, anything Joe or Zach you want to add to that? >> Uh, you know, something Luly was saying that I think carries through is is that that that merger of the two, we're also seeing it reflected organizationally. Um, the chief data officer and the CIO are now starting to report to COS. >> Um, and the idea is, you know, a lot of your content and unstructured stuff was managed by it. A lot of your data was managed elsewhere. you need both to make AI work and you need someone to report up to for that. So, uh we we've definitely started to see and it happened in the last year. >> Yeah, like a couple of rewards um as a result of that. >> Yeah, it's starting to to move that way and I think that that's something that anyone looking for a career in data should be thinking about. >> Well, that cues up my next question. uh very nicely. So do you see the importance of data management and the number of jobs working in data increasing or decreasing over the next 10 years which 10 sounds so far away now um um but and why? >> Yeah, I I will speak at least from the services side. I think that uh everybody's seen the news uh big layoffs and services organizations many attributed to the fact that AI is doing the work of analysts and these different companies. We're seeing the opposite. Uh what we see because of the niche that we're in is is growth. uh the number of calls and the number of calls from large global Fortune 500 type organizations is actually increased dramatically with a much greater sense of very specifically what they want and need which is to make their AI trustworthy and work and leveraging semantics. So we're hiring and we we predict growth for for the the the near future. I don't know that I'm going to say 10 years because I think I don't know what's happening in five, but for the next several years, we have a pretty confident path. >> Very nice. Oh, well, this has been such a pleasure to chat with all of you. Um, thank you so much for joining as a group. I love group interviews. It's so fun >> your stories. >> Um, and I want to make sure that everyone checks out your book, Bridging Knowledge, Data, and AI: Harnessing the Semantic Layer Framework to Drive Intelligence. I'll put a link on the podcast site to uh to purchase the book to the book. And if uh just to ask, and I'd be remiss if I didn't ask, if anybody had questions about enterprise knowledge and how to engage with you, where would they find you? Uh, easiest way is to email us at info@enterprisenowledge.com. >> I love it. All right. Well, Lily, Joe, and Zach, thank you so much for taking the time today. And, uh, to everyone out there, um, we will post a link again to purchase the book on the website. And for all of our listeners, if you'd like to keep up to date in the latest podcast and in the latest in data management education, you may go to data.net/subscribe. Until next time, stay curious, everyone. >> Thank you, Shannon. Yeah. >> Thank you. >> Thank you, Shannon. [music]