#107 Focusing on Outcomes and Building Brave Teams in Data - Interview w/ Gretchen Moran

https://www.patreon.com/datameshradio (Data Mesh Radio Patreon) - get access to interviews well before they are released Episode list and links to all available episode transcripts (most interviews from #32 on) https://docs.google.com/spreadsheets/d/1ZmCIinVgIm0xjIVFpL9jMtCiOlBQ7LbvLmtmb0FKcQc/edit?usp=sharing (here) Provided as a free resource by DataStax https://www.datastax.com/products/datastax-astra?utm_source=DataMeshRadio (AstraDB); George Trujillo's contact info: email (george.trujillo@datastax.com) and https://www.linkedin.com/in/georgetrujillo/ (LinkedIn) Transcript for this episode (https://docs.google.com/document/d/15QaPbgVvALLawq19qe62-CRxVFbawjo1BGOrvt9rX3g/edit?usp=sharing (link)) provided by Starburst. See their Data Mesh Summit recordings https://www.starburst.io/learn/events-webinars/datanova-on-demand/?datameshradio (here) and their great data mesh resource center https://www.starburst.io/info/distributed-data-mesh-resource-center/?datameshradio (here) In this episode, Scott interviewed Gretchen Moran, the Senior Director, Data Products at the National Geographic Society (NGS; the non-profit arm of National Geographic). Some key takeaways/thoughts from Gretchen's point of view: NGS is a bit unique in that they don't have a widely deployed data architecture so they do not have a lot of habits to unlearn. Starting with a greenfield means likely more training and learning/experimenting will be required but at least no institutional unlearning. To move forward with data mesh, organizations must be able to embrace change - and the pain that it will inevitably bring - and embrace ambiguity. You need to move forward and figure it out together but also be okay with failure as a learning experience as you test what works for your organization. To win the hearts and minds of data producers, show them what high-quality data can mean for the organization and their domain/role. Work closely with them, understand their context, hold their hand to bring them along and align them to the vision of data