#224 Building Out Scalable Automated Access for Data Mesh at Disney Streaming - Interview w/ Himateja Madala

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.Himateja's LinkedIn: https://www.linkedin.com/in/himatejam/Himateja's AWS ReInvent presentation (link starts at her part): https://youtu.be/y1p0BGsPxvw?t=1991In this episode, Scott interviewed Himateja Mandala, Senior Data Engineering Manager and Head of the Data Mesh Data Platform at Disney Streaming. To be clear, she was only representing her own views on the episode.Some key takeaways/thoughts from Himateja's point of view:?Controversial?: Your existing data platform(s) might not be able to serve data mesh well, even with reasonable augmentation - especially if your data platform has become hard to change. You might have to build from scratch.When the data platform's key users aren't part of the centralized team, you need to think about enabling automated capabilities by default, e.g. security the second data lands or easy to leverage and understand monitoring/observability.?Controversial?: Data products serving different use cases often end up looking relatively different. Is your data product for dashboards and reporting/analytics; is it for serving a recommendation engine or machine learning model; or is it more for internal usage? Be okay with data products not being uniform.Even if your data mesh platform operates outside the traditional paradigms, many data producers - especially data engineers - will still be thinking data pipelines. Be prepared for that, it's an ingrained way of thinking for many.Data contracts are very helpful in defining and maintaining quality. If you set up good observability on your data products, owners can quickly identify when there

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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