#189 Our Data is In the Cloud… Now What? - Interview w/ Vikas Kumar
Data Mesh Radio - Un pódcast de Data as a Product Podcast Network
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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...