#67 All About Interoperability and Standards in Data Mesh - Interview w/ Samia Rahman

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.Samia's LinkedIn: https://www.linkedin.com/in/samia-rahman-b7b65216/FHIR standard cheat sheet: https://www.healthit.gov/topic/standards-technology/standards/fhir-fact-sheetsIn this episode, Scott interviewed Samia Rahman, Director of Data and AI Strategy and Architecture at life sciences company Seagen. Samia is helping to lead Seagen's early data mesh implementation after helping with two implementations at Thoughtworks since the start of 2019.For Samia, interoperability is about taking information from two systems and combining them to get a higher value. A simple definition but a good one.Two potential key takeaways: 1) don't try to plan too much ahead for developing interoperability standards but definitely keep an eye out for places where you could start to develop those standards. And your standards really, really should evolve - you don't have to nail them right out of the gate. 2) your interoperability will also evolve - you don't need to make every data product interoperable with every other data product and you can start with basic interoperability first. The more you can standardize around unique identifiers, the better, but it's okay to not get it right first thing out of the gate.Samia started her career - and even before in school - focusing on software, especially end-to-end development. A repeating pattern for her has been how crucial contract testing is to getting things into a trustable and scalable state. We've had them in hardware and software for a long time and if you don't have easy testing, those systems often get replaced pretty quickly. Those tests are the safety net to allow for fast and reliable evolution. And that evolution is a key theme for this conversation - set yourself up to iterate and evolve as you learn. Work to not paint yourself in a corner Data standards, including specifically for interoperability, are everywhere in the life sciences space - FHIR, FDA has lots, etc. but it's still not great for truly sharing the meaning of the data. FAIR is trying to get there but the interoperability and domain...