By Marydee Ojala
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Chief data officer at Customer ThriveData, Chantel Wilson Chase, used her background in mathematics in her session that closed out the Analytics & Semantic Layers track at the Data Summit 2026 conference.
The annualData Summitconference returned to Boston, May 6-7, 2026, with pre-conference workshops on May 5.
She took a very different approach to analytics, focusing on the missing data in any and all problems and shared a formula she created about measuring moments in our lives.
As a data scientist and mathematician, she builds equations, so she wanted an equation for those “Aha moments” we’ve all experienced.
“We measure everything,” she said, “but we don’t have good measures for life itself.” Life is moments that are infinitely close together. Three layers contribute to measuring those moments: operational data, perception data; and inverse data. Added together, these layers form the basis of her Wilson Life Formula.
Operational data is structural, findable, and collectable, while perception data is gained by asking questions of subjects. Perception is data but it can be subjective. Inverse data encompasses negative space and unseen impact.
Wilson Chase cited two methods of measuring inverse data. One she called the Wald Method, drawn from mathematician Abraham Wald’s realization during World War II that by analyzing only damage to planes that had not been shot down, half the population had been ignored and incorrect assumptions made. Instead of reinforcing areas of the plane with bullet holes, reinforcing those not damaged resulted in fewer losses. This is now known as survivorship bias.
The Black Hole Method is used by astrophysicists, who study black holes by measuring everything around it. The Wald Method tells us to look at the whole picture. The Black Hole Method encourages us to study the impact of what is around a moment.
We can measure a moment accurately but how it plays out in real life is different. Metrics provide an outline but even if you know all the data that exists, it’s not necessarily going to lead to accurate assessments of impact. This is where the value of inverse data comes in. Particularly in today’s AI environment, she reminded us that not all data looks like data.
Many Data Summit 2026 presentations are available for review athttps://www.dbta.com/datasummit/2026/presentations.aspx.