Customer stories
Three data teams, three kinds of late.
The companies below are fictional. Their stories show the kind of result a data team can expect, with numbers measured the way we would measure them in a real account.
Freight and logistics, 1,400 employees, 9 person data team
How a freight marketplace stopped finding out about late shipment data from its own customers.
Consumer lending, 600 employees, 6 person data and finance systems team
A lender made month-end reporting predictable by seeing which source feeds were late before the close began.
Online grocery, 2,200 employees, 14 person data team
A grocery delivery company used lineage to find the real blast radius of a broken model in minutes instead of hours.
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