The Impact of LLMs on Data Transformation Processes

Katariina Kari For the past eight years, Katariina Kari has built knowledge graph teams at giant e-commerce companies like IKEA and Zalando. This practical, real-world experience puts her in an elite group of ontology and knowledge graph experts. Knowledge graphs offer unique benefits to e-commerce merchants. From better product recommendations to more useful search results, the semantic capabilities that knowledge graphs provide routinely result in seven-figure sales increases. The knowledge graphs that Katariina builds provide a semantic layer in the enterprise architecture that lets companies capture, use, and re-use the organization's unique domain knowledge in any number of applications. Because knowledge graph isn't one application that does one thing. It's a paradigm shift in the way we work with data. It's a paradigm shift in the way we code, because now you don't need to put business logic into your code. We talked about: her work over the past eight years building knowledge graphs at companies like IKEA and Zalando how using knowledge graphs to improve reccomendation and search routinely brings seven-figure business benefits the set of skills and talents it takes to implement a knowledge graph project, most of which already exist in most companies how LLMs and other AI tools can help transform structured or unstructured data into semantic data, a computable resource that captures business domain knowledge some of the specific skills needed for KG work: ontology experts, back-end developers who understand the semantic web stack, data scientists and engineers, knowledge practitioners to capture domain knowledge, and product management the need in each organization for a unique knowledge graph team tailored to the needs of the company and the talent available the importance of user-centricity and use-case understanding in any knowledge graph project the benefits of capturing business logic in a semantic layer which can be used and re-used in multiple applications an interesting search-improvement use case that resulted in seven-figure sales increases, as well as experience-improving recommendation and info-box use cases how capturing subject matter expertise in a knowlege graph can dramatically improve recommendation systems and deliver unexpected benefits to other the importance of showing the benefits of knowledge graphs to organically advance enterprise adoption her take on the difference between RDF-based knowledge graphs and labeled property graphs (LPGs) like Neo4j the compelling case for knowledge graphs in e-commerce, which she has discovered in her eight years of practice Katariina's bio Katariina Kari is a leading expert in semantic web technologies, specializing in the development of ontologies and knowledge graphs. Over the past eight years, she has worked with prominent brands like IKEA and Zalando, building knowledge graphs that significantly enhance customer experiences by improving search functionalities and recommendations. Her extensive hands-on experience in creating enterprise knowledge graphs has established her as one of the global top talents in the field. Katariina is frequently invited to speak at international events on the semantic web and knowledge graphs, sharing her insights and practical expertise with industry professionals. Her deep knowledge and passion for the semantic web have made her a sought-after keynote speaker and thought leader in the field. Balancing a dual enthusiasm for technology and the arts, Katariina holds both a Master of Science degree and a Master of Music degree. From 2012 to 2016, she ran her own consultancy, where she worked closely with classical music organizations and artists, helping them navigate digital outreach. An art-loving and art-serving nerd, she seamlessly blends her love for music and technology in all her work, constantly pushing the boundaries of what’s possible in her field. Connect with Katariina online LinkedIn Video Here’s the video version of our conversation: https://youtu.be/gMFAHlY7VL0 Podcast intro transcript This is the Knowledge Graph Insights podcast, episode number nine. One of the main benefits of semantic technology is the ability to sort out business logic independent of data and data from the applications in which it's used. Katariina Kari has captured in knowledge graphs the business expertise of e-commerce giants like IKEA and Zalando to power better search and recommendation systems and to generally provide a better experience for both internal users and external customers, resulting in millions of dollars in new sales. Interview transcript Larry: Hi, everyone. Welcome to episode number nine of the Knowledge Graph Insights Podcast. I am really delighted today to welcome to the show Katariina Kari. Katariina is a long-time, deeply embedded in the community knowledge graph professional. She's done a lot of e-commerce work at places like IKEA and Zalando. She's currently the head of data at a stealth internet, a stealth startup that we can't talk too much about. But welcome, Katariina. Tell the folks a little bit more about what you're up to these days. Katariina: Yeah, thank you Larry, and thank you for having me in your podcast. Yeah, I could say that I've been really lucky to have worked in the industries and especially in the lifestyle sector, e-commerce sector for the past eight years. So very early on, before even graph databases were really commercialized, I had the opportunity to start building knowledge graphs. And so now, when there's someone out there was like, "Oh, I need a knowledge graph," I can confidently say, "Well, I've done it a few times so I can tell you, I can advise you or I can even run a team for you that can build the knowledge graph." And it's just shown me a lot of practical things, it's given me a really good perspective on what works from theory and from research and what actually doesn't, or doesn't yet work, or isn't mature enough yet for an applied setting in commercial use. Larry: That point you just brought up, you have a PhD in something, right? Katariina: No, no, I don't have a PhD. I never really went into research. I have a few published articles, scientific articles that I did towards the end of my master's, but I actually just have two master's. I have a master's in technology and then I have a master's in music arts management, because I've always carried this love for both art as well as technology, and I always wanted to combine them. Larry: I didn't plan it this way, but the episode right before this one, number eight, was Vera Brozzoni, who's a metadata strategist at the BBC, and she comes out of classical music. So if you don't know Vera, you two have to meet and talk music and data and stuff. But one of the things you mentioned there is one of the things in this community is, and the reason I assumed, it's usually safe to assume in this world that somebody has a PhD, but you've always been more focused on the practice side than the research side, which is awesome, because I'm all about sharing practice, so thank you for being focused that way. And you have all this experience coming up on, what, eight years of experience at IKEA and Zalando, two of the biggest retail brands in the country, or in the world. Larry: And one of the things, and I want to gently take you to task for something in a talk I saw you do recently, this hour-long talk, brilliant stuff about a lot of this stuff we'll talk about today, but right in the middle of that talk, you just kind of matter-of-factly mentioned like, "Yeah, and we're realizing seven-figure business benefits across this." I'm like, "Wait, what?" And in my journalism training, we would call that burying the lede. But that's kind of at a top level... There's real obvious business benefits to adopting knowledge graph technology. Can you talk about what is it that's unique about the work you've done and this technology that permits these massive revenue gains? Katariina: I would say that one part of it is the work, but the other part of it is working with big brands like Zalando, Europe's biggest e-commerce fashion, and then IKEA, one of the most known trademarks or brands in the world. So their volumes in e-commerce are huge. So if you add a positive change to the customer experience, like giving quality recommendations or just improving a few of the worst-performing search terms, you get a lot of... The volume is so big, the benefit is really big, and it's already in that category of seven-figure sums. So that's why I think maybe not every little e-commerce site can invest in this technology first. It's great that these big brands are actually investing in so we can figure out exactly how to do it, and then that can be brought to maybe a smaller-volume e-commerce setting or smaller-volume industry so that they can then make sense of these best practices. That's at least the way I see it. But yeah, I mean just being able to improve a big website's performance, just doing little optimization is already moving the needle quite a lot. Larry: Right. And once you've articulated those best practices, you can picture it, smaller businesses benefiting from it. But right now, it takes quite a team to put this together. I've heard you talk a lot about the skills that it takes, the roles that you need to execute on those skills, and then the human element, the thing that our friend Ashleigh Faith calls the data therapy part of this. Can you talk a little bit, I guess, first, about what does it take, what are the skills that you need, the knowledge, the wherewithal in your organization to actually make a knowledge graph project like the ones you've worked on happen? Katariina: Well, when you work with these industries in e-commerce, they'll probably have already very brilliant backend developers,