Minimum viable (data) product: Bringing a product mindset to analytics engineering with dbt and Deepnote

Analytics work mirrors product development: identify a user need, build a minimum viable product to address that need, evaluate the impact and iterate. In this talk, Michal Kolacek, analytics engineer at Slido describes how MVP-like thinking can help data teams counterbalance and complement the standardized approaches of dbt.

We will walk through Slido’s evolution in their approach, tooling and the vision of building better data products using Deepnote notebooks. Finally, we will take a look under the hood of the new dbt integration in Deepnote and outline how data teams can use it to accelerate model prototyping and metrics workflows.