#135 Iterating Consciously - and Quietly - Towards Data Mesh Capabilities - Interview w/ Balvinder Khurana

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. You can download their Data Mesh for Dummies e-book (info gated) here.Balvinder's LinkedIn: https://www.linkedin.com/in/balvinder-khurana/In this episode, Scott interviewed Balvinder Khurana, Principal Data Architect at Thoughtworks.Some key takeaways/thoughts from Balvinder's point of view:Data mesh is NOT a silver bullet and not everyone is ready to do data mesh - others have stated that but it's crucial to repeat.A data mesh doesn't happen in a vacuum - you need to assess if you are really ready and does it align first to your business strategy and second to your data strategy.If you decide to move forward on a data mesh implementation, really consider how you will measure progress and success against business goals.To evaluate data mesh appropriately, consider what business value having better data practices would bring to your company and is your company aligned into lines of business or would you need to reorganize your business. Are you prepared to extend your line of business practices to data?A common failure pattern in analytics has been not looking at the Intelligence Cycle - changing your operational systems and processes as a result of insights. Don't just generate insights, insights must generate action! Data mesh must avoid this too.Even if existing centralized data team setups have significant bottlenecks, data consumers typically eventually get their needed data. Those data consumers can see something like data mesh as a risk - will they still be able to eventually get the data they need? Is eventually getting to faster access to new data worth the perceived risk?If you have resistance to data mesh, look at delivering necessary capabilities to your data producers and/or consumers in a...