Finding the Data Is Half the Job
An analyst searches for revenue and gets forty results. The search worked. The next twenty minutes — deciding which table to trust — is the part nobody designed.
Enterprise search gets measured on relevance. Did the right rows come back, how fast, ranked how well. By that measure the system I was asked to look at worked fine.
It was still costing people their afternoons.
Forty Results Is Not an Answer
An analyst searches revenue and gets forty results back. Then the real work starts. Which table is current. Which one was deprecated but never deleted. Which one the finance team actually uses. Which one has the definition of revenue this question needs.
That is twenty minutes of asking colleagues, opening tables, and eventually picking one on a hunch. The search took half a second. The decision took the rest of the morning.
Trust Is a Design Problem, Not a Data Problem
The instinct is to fix this upstream — better governance, cleaner catalogues, someone to deprecate old tables properly. Worth doing, and it never finishes. Meanwhile the analyst still has forty results.
The design answer is different: put the trust signals on the result, where the decision is being made. How fresh is it. Who owns it. How many people query it. Is it certified. Does it look abandoned.
None of that's new information. It exists in the metadata already. It was just kept somewhere the person deciding never looked.
The Question Behind the Question
Every search interface assumes the user's question is "where is it". Often the real question is "which of these should I believe". Those need different screens.
If your users routinely find something and then go and ask a human whether to trust it, that conversation is a missing feature, not a cultural quirk.
What I built, the two calls that changed it, and what I got wrong are in the DAE Search case study.
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