#57 Using a Knowledge Graph for a Data Marketplace and Data Mesh for Retail - KGC Takeover Interview w/ Olivier Wulveryck and Guest Host Ellie Young

Sign up for Data Mesh Understanding's free roundtable and introduction programs here: https://landing.datameshunderstanding.com/Please Rate and Review us on your podcast app of choice!If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see hereEpisode list and links to all available episode transcripts here.Provided as a free resource by Data Mesh Understanding / Scott Hirleman. Get in touch with Scott on LinkedIn if you want to chat data mesh.Transcript for this episode (link) provided by Starburst. See their Data Mesh Summit recordings here and their great data mesh resource center here.Ellie's LinkedIn: https://www.linkedin.com/in/sellieyoung/Olivier's LinkedIn: https://www.linkedin.com/in/olivierwulveryck/Knowledge Graph Conference website: https://www.knowledgegraph.tech/Free Ticket Raffle for Knowledge Graph Conference (submissions must be by April 18 at 11:59pm PST): Google FormIn this episode of the Knowledge Graph Conference takeover week, special guest host Ellie Young (Link), founder of Common Action, interviewed Olivier Wulveryck, Senior Consultant and Manager at OCTO Technology.In the first two thirds of the interview, Olivier and Ellie chatted about a lot of concepts specifically around data mesh and then they linked in the concepts around knowledge graph in the last third.For Olivier, a knowledge graph is the map for the data that is available - each data product or node in a data mesh is the representation of the knowledge within the organization. The knowledge graph is the abstraction of that knowledge across the data mesh - a logical representation on top of the data mesh nodes to help people make sense of the data mesh.Currently, Olivier is working with a client sharing their data in a data marketplace. They are working on implementing a knowledge graph on that but not on their internal data. If they are seeing value from applying a knowledge graph externally, they may apply to their internal usage.Olivier shared his view that it's easier to start with a data mesh than a knowledge graph - any first steps with a data mesh will bring you value. It is not the same with knowledge graphs - you have to do more work to get to value with knowledge graphs.Olivier previously worked on the operational side of software engineering. He realized they had lots of data sitting in databases but the data was just a consequence - it was state data, there was no temporal dimension. He wanted...

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Interviews with data mesh practitioners, deep dives/how-tos, anti-patterns, panels, chats (not debates) with skeptics, "mesh musings", and so much more. Host Scott Hirleman (founder of the Data Mesh Learning Community) shares his learnings - and those of the broader data community - from over a year of deep diving into data mesh. Each episode contains a BLUF - bottom line, up front - so you can quickly absorb a few key takeaways and also decide if an episode will be useful to you - nothing worse than listening for 20+ minutes before figuring out if a podcast episode is going to be interesting and/or incremental ;) Hoping to provide quality transcripts in the future - if you want to help, please reach out! Data Mesh Radio is also looking for guests to share their experience with data mesh! Even if that experience is 'I am confused, let's chat about' some specific topic. Yes, that could be you! You can check out our guest and feedback FAQ, including how to submit your name to be a guest and how to submit feedback - including anonymously if you want - here: https://docs.google.com/document/d/1dDdb1mEhmcYqx3xYAvPuM1FZMuGiCszyY9x8X250KuQ/edit?usp=sharing Data Mesh Radio is committed to diversity and inclusion. This includes in our guests and guest hosts. If you are part of a minoritized group, please see this as an open invitation to being a guest, so please hit the link above. If you are looking for additional useful information on data mesh, we recommend the community resources from Data Mesh Learning. All are vendor independent. https://datameshlearning.com/community/ You should also follow Zhamak Dehghani (founder of the data mesh concept); she posts a lot of great things on LinkedIn and has a wonderful data mesh book through O'Reilly. Plus, she's just a nice person: https://www.linkedin.com/in/zhamak-dehghani/detail/recent-activity/shares/ Data Mesh Radio is provided as a free community resource by DataStax. If you need a database that is easy to scale - read: serverless - but also easy to develop for - many APIs including gRPC, REST, JSON, GraphQL, etc. all of which are OSS under the Stargate project - check out DataStax's AstraDB service :) Built on Apache Cassandra, AstraDB is very performant and oh yeah, is also multi-region/multi-cloud so you can focus on scaling your company, not your database. There's a free forever tier for poking around/home projects and you can also use code DAAP500 for a $500 free credit (apply under payment options): https://www.datastax.com/products/datastax-astra?utm_source=DataMeshRadio