#198 How Do We Make Data Contracts Easy, Scalable, and Meaningful - Interview w/ Ananth Packkildurai

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.Ananth's LinkedIn: https://www.linkedin.com/in/ananthdurai/Schemata: https://schemata.app/Data Engineering Weekly newsletter: https://www.dataengineeringweekly.com/In this episode, Scott interviewed Ananth Packkildurai, Author of Data Engineering Weekly and the creator of Schemata.Scott note: we discuss Schemata quite a bit in this episode but it's an open source offering that I think can fill in some of the major gaps in our tooling and even ways of working collaboratively around data.Some key takeaways/thoughts from Ananth's point of view:!Important!: Collaboration around data is crucial. The best way to get people bought in on collaboration around data is to integrate into their workflow, not to create yet another one-off tool in yet another pane of glass.?Controversial?: There is so much friction between initial data producers - the domain developers - and data consumers because they are constantly speaking past each other. The data consumers have to learn too much about the domain and the data producers rarely really understand the context of most analytical asks.Data creation is a human-in-the-loop problem. Autonomous data creation is not likely to create significant value because the systems can't understand the context well enough right now.As Zhamak has also pointed out, there is far too much tool fragmentation. It made sense with lots of readily available VC money and finding how to approach things with cloud but we need holistic approaches, not spot approaches to things...

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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