#174 Measuring the Impact and Value of Your Data Products in Data Mesh - Interview w/ Pink Xu

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.Pink's LinkedIn: https://www.linkedin.com/in/pink-xu/In this episode, Scott interviewed Pink Xu, Change Manager of Business Impact of Data Products at Vista.Before we jump in, there are a few specific examples in this to Vista but I think it is incredibly relevant when looking at measuring the impact of your data work. As Pink says, set the objective/goal for the data product and then measure if it met that objective/goal. It isn't the impact framework's job to specifically measure if the objective of the data product is valuable, only to provide an objective way to measure how well did the data product meet its goal. Some key takeaways/thoughts from Pink's point of view:Look to standardize the way you measure impact for data products. Much like data observability/SLA metrics, a centralized team shouldn't be the ones focused on measuring or defining the target impact of a data product, only providing the way to measure it.Again like data observability, an impact measurement framework/methodology means people can trust exactly how impact was measured without having to dig into every measurement decision. It's not like grading your own essay, which is a problem with a not impartial measurement.Impact measurement can only go so far. It shouldn't be the only consideration in valuing a data product but without a fair, impartial framework, measuring the value of work becomes all the more difficult.A data product "enables business impact", it cannot create the impact itself if no one uses it. Think about who gets "credit" for the impact - is it the data product creator or the team that acted on the insights from the data product? Look to reward/credit...

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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