#99 Getting Philosophical About Knowledge and Sharing Experiences via Data - Interview w/ Andrew Padilla

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.Andrew's LinkedIn: https://www.linkedin.com/in/andrew-padilla-8988094a/Datacequia website: https://www.datacequia.com/Andrew's personal Substack: https://datacequia.substack.com/Data Mesh Community newsletter Substack: https://datameshlearning.substack.com/In this episode, Scott interviewed Andrew Padilla, who runs a data and software consulting company - Datacequia - and serves as editor of the Data Mesh Learning community newsletter.This one is a bit more philosophical about sharing information/knowledge so it's one to sit and think over. Things in quotes are direct from Andrew.Some key takeaways/thoughts that come from Andrew's view of data mesh and the data space in general:To move from sharing the 1s and 0s of data to actually sharing knowledge, we need to harmonize data, metadata, and code - "the digital embodiment of knowledge". That's where Andrew hopes the mesh data products can head.Software development isn't cutting it for sharing knowledge. Will data product development? Do we need to move to knowledge-centered development instead? Remains to be seen.We still don't know how to model well - in data - what is going on in the real world. What are the experiences of the organization? Can we really define an "organizational experience"? Event storming tries but seems to fall short often.We must learn to treat organizations like living entities. Organizational experiences cross multiple domains and the types of experiences will change, will evolve - possibly quite quickly. We again have to get better at modeling those and evolving how we share knowledge about the experiences.Knowledge graphs are the best way we have currently for combining information across domains. We still haven't fully figured out how to leverage our cross domain knowledge though.Historically, we've bent our ways of working to the limitations of the machines. We need to spend more...