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Summary: Guiding the evolution of data mesh with fitness functions
We recently hosted an insightful discussion on data mesh with Zhamak Dehghani and Dave Colls. The audience asked some great questions during the session around a few key topics. One of our presenters, Dave Colls, has captured these in this summary.
Active learning loops
At ThoughtWorks we're starting to see patterns of how people integrate various mixes of labelled and unlabelled data into systems. We're finding it needs careful planning and explicit loops to manage the different data flows. There are many questions though; At what point do you decide to introduce models around unlabelled data? How do you validate that it's worth the cost? These are all interesting questions that change from system to system!
Metric-driven Data Architectures
It is common for organisations to use multiple BI tools, such as Tableau and Power BI, in order to meet the specific reporting needs of different teams. However, when crucial business metrics (such as monthly recurring revenue and customer churn rate) are defined and maintained in multiple locations, serious risks surrounding their discoverability, agreement, and correctness can arise.