#64 The Crucial Value of Data About Your Data: Approaching Data with a Product Mindset - Interview w/ Sadie Martin

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 hereSadie's LinkedIn: https://www.linkedin.com/in/sadie-martin-06404125/In this episode, Scott interviewed Sadie Martin, Senior Product Manager, Data Platform at Q4 Inc about applying a product mindset to data in general. This is really crucial to getting data as a product right but also in building out your data platforms and even some processes for data mesh.Scott's summation of some key points:Anyone can apply a product mindset, not just the product managerGiving yourself the time before starting work to investigate and create you measurement framework, including your baselines, is crucial to measuring data work progress and choosing where to focusApproach your data work with intentionalityReally understand what you are trying to accomplish and what your immediate customers/consumers are trying to use the data for to accomplish.Sadie started as a data analyst where the team didn't have a product manager - they were doing a lot of work and weren't sure if things were likely to work or even if what they did had a positive impact after it was done. So she started to take on some of the task of answering those questions and transitioned into being a product manager for data. So, what is a product mindset? For Sadie, the easy definition but with lots of hidden depth, is "it's all about really understanding the problem". For most organizations, really thinking about the problem you are trying to solve is new relative to data. There may be a data request but what product or process is that data contributing to and what is that product or process trying to solve? Sadie believes measuring the problem is really crucial. Once you figure out what you are trying to solve, what is the scope of the problem? How are you going to measure if you are actually solving the problem? Especially is it better than what you were previously doing? She also talked about the importance of customer-centricity - really why are they making a data ask? Should this really be a one-off or a repeatable process? Did they ask for the complete set of what they need? Etc.One crucial insight Sadie has brought from product management to data is to be willing and ready to throw things...