#112 Driving Buy-In and Finding Early Success - Kiwi.com's Data Mesh Journey - Interview w/ Martina Ivaničová

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.Martina's LinkedIn: https://www.linkedin.com/in/martina-ivanicova/In this episode, Scott interviewed Martina Ivaničová, Data Intelligence Engineering Manager at the travel services company Kiwi.com.Some key takeaways/thoughts from Martina's point of view:The most important - and possibly one of the most difficult - aspect of a data mesh implementation is "triggering organizational change". Driving buy-in for something like data mesh is obviously not easy. As you are getting started, look to leverage 1:1 conversations to really share what you are trying to do and why and how this can impact them and the organization. These 1:1 conversations are crucial to developing early momentum.On driving buy-in for data mesh, really think about how to limit incremental cognitive load as much as possible on developers/software engineers. If you can keep cognitive load low, you are much more likely to succeed - succeed in driving buy-in and succeed in delivering value.When sharing internally about data mesh, it's important to focus on what it means to the other person. Using "data mesh" as a phrase can lead to a lot of confusion for people not on the data team. Make it clear what you are trying to accomplish - the what, the why, and the how. Using data-as-a-product as the leading concept resonated and worked well.Kiwi.com started driving buy-in by working with the engineering upper management, then found a few valuable and achievable first use cases to move forward. And they have kept cognitive low on the engineering teams while they learn how to deliver data as a product.If possible, the easiest way to drive buy-in is by finding a use case that is beneficial to the producing domain. If not, then look to spend the 1:1 time to really share why this matters.Kiwi.com is getting software engineers in domains to commit to simply sharing their data, not even really structuring into data products. So the software engineers in most cases are really only focused on maintaining high-quality data sharing mechanisms - read: pipelines. That is a relatively low initial cognitive load/low workload ask.Analytics engineers are creating the data products from the sourced data to...

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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