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Tagged: AI Data Explorer

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One Dataset, Several Stories: What AI Data Explorer Actually Does With Clean Data

Posts on this blog covered Data Explorer fixing broken shapes: data with no value column, data spread across four stage columns instead of a proper flow. Both are real problems Data Explorer solves. But most of the time, your data isn't broken. It's already sitting there as a clean Source, Target, Value table, ready to go.

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Beyond Source and Target: Turning a Four-Stage Dataset Into a Top 5 Slide Deck

Most Sankey examples show two columns: a source, a target, done. But almost nothing in the real world only has two stops. A customer doesn't just go from "ad" to "purchase," they land somewhere, browse on some device, look at some category, and end up at some outcome. A hiring pipeline isn't "applied" to "hired," it's source, screen, interview, offer. Real journeys have stages, plural.

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