#50 Evaluating if Data Mesh is a Fit; Team Structures; and WTF is Federated Computational Governance - Interview w/ Marius Ingjer

Provided as a free resource by DataStax https://www.datastax.com/products/datastax-astra?utm_source=DataMeshRadio (AstraDB) https://www.patreon.com/datameshradio (Data Mesh Radio Patreon) - get access to interviews well before they are released Transcript for this episode (https://docs.google.com/document/d/1A4r9SkQP_x6ppIph_WGQxiKh3dDoY8f4hQ-OBJ0w0Xc/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 Marius Ingjer, Co-founder and Senior Consultant at Knirkefritt AS. Marius has been working with a few clients on implementing data mesh. They covered 3 distinct topics: evaluating if data mesh is a fit for your organization, team structure challenges in data mesh or data mesh-like implementations, and a simplified definition of federated computational governance. Evaluating if data mesh is right for you: To start, Marius provided a list of evaluation questions to help you determine if data mesh might be right for you: How many data sets are you producing? What is the lead time to creating a new dataset? How well are your datasets serving your data needs? How many domains do you have? How complex are your domains? How does the team respond to new data requirements? How usable in general is your data? Every company wants to share data well but the centralized data team isn't the bottleneck yet for many. Centralization can add a lot of value until it starts to become more hurtful than helpful and yes, figuring out that point is easier said than done. Centralization of data fights Conway's Law and can become way too much cognitive load so it will eventually become an issue for many organizations. A key question in evaluating if data mesh is a fit: what is the cost of allowing your data processes to fail? Per Marius,