#189 Our Data is In the Cloud… Now What? - Interview w/ Vikas Kumar

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.Vikas' LinkedIn: https://www.linkedin.com/in/vksnov9/Vikas' Twitter: @vikaskumar9 / https://twitter.com/vikaskumar9Vikas' email: vikaskumar9 [at] gmailIn this episode, Scott interviewed Vikas Kumar, AVP and Head of Data, AI, and ML at CNA Insurance. To be clear, he was only representing his own views in this episode.Some key takeaways/thoughts from Vikas' point of view:In data mesh, make sure to keep focused on bringing the business domains along. You aren't building for the sake of building. If users can't derive value from the data work being done, why is it being done?The 2010s through the early 2020s have been about moving data to the cloud but we are starting to see people really leverage that data to generate value. The cloud unlocks many new possibilities around data due to flexibility, scalability, and unit economics.With moving to cloud, there is much less focus on specifically managing the data and more focus on getting value from the data. SaaS data product offerings really unlock people's time to focus on driving value.Cloud gives us the scale and data availability but there is still a long way between having the data available and leveraging the data for significant value.Cloud can be a double edged sword - it gives you flexibility and scalability but without good controls, you are likely to do a lot of duplicate work. Be careful that ease of data product creation - or at least PoC creation - doesn't create chaos and data product overlap. Make sure to have good governance here including strong communication.?Controversial?: We aren't very good...

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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