#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...