MVA: Minimum Viable Analysis

What it means, how to use it in practice, and why you need it

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Data scientists are detail-oriented by nature. You’ve probably noticed that by now. And can you blame us? We spend our time pouring over granular datasets, finding mistakes, cleaning them, building predictive models, producing visualizations, deriving insights, and communicating those insights to stakeholders in…