If you don't standardize how you work, you can't scale effectively.
Workflows turn ad-hoc work into templates your team can execute. This helps you spread better ways of working. Improve team autonomy, velocity, quality, and consistency.
Execute data science workflows effectively. Recall fewer systems from prod. Deal with less unacceptable and unexpected behavior.
Projects move quickly from concept to production with clear expectations and requirements, coordination, and high visibility.
Follow predictable standards and best-practices that everyone agrees on.
Known data failure modes are analyzed and small steps are constantly taken to prevent them.
An automated papertrail of how your people, processes, and tools worked together.
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