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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

Dave's LinkedIn: https://www.linkedin.com/in/davidcolls/

Zhamak's data mesh book: https://www.oreilly.com/library/view/data-mesh/9781492092384/

Building Evolutionary Architecture book: https://www.oreilly.com/library/view/building-evolutionary-architectures/9781491986356/

Team Topologies book: https://teamtopologies.com/book

The Agile Triangle regarding helping you decide how thin to slice: https://www.projectmanagement.com/blog/blogPostingView.cfm?blogPostingID=5325&thisPageURL=/blog-post/5325/The-Agile-Triangle#_=_

In this episode, Scott interviewed Dave Colls, Director of Data and AI at Thoughtworks Australia. Scott invited Dave on due to a few pieces of content including a webinar on fitness functions with Zhamak in 2021. There aren't any actual bears, as guests or referenced, in the episode :)

To start, some key takeaways/thoughts and remaining questions:

1. Fitness functions are a very useful tool to assess questions of progress/success at a granular and easy-to-answer level. Those answers can then be summed up into a greater big picture. You should start with fitness functions early in your data mesh journey so you can also measure your progress along the way. To develop your fitness functions, ask "what does good look like?"
2. Focus your fitness functions on measuring things that you will act on or are important to measuring success. Something like amount of data processed is probably a vanity metric - drive towards value-based measurements instead.
3. Your fitness functions may lose relevance and that is okay. You should be measuring how well you are doing overall, not locking on to measuring the same thing every X time period. What helps you assess