Listed employees
829
Complete population represented in the source disclosure.
Data engineering and analytical storytelling
A portfolio case study showing how a structured disclosure can become a validated, interactive decision experience while preserving privacy and clearly communicating statistical limitations.
The analytical challenge
The source contained 829 anonymous employee records across 144 exact job titles. The workflow reconciled every row, defined the outcome carefully, grouped ages, calculated comparison rates and uncertainty, then removed granular records before publication.
Interactive cohort view
Age-band selection changes the headline metrics and eligibility composition.
Listed
829
Eligible
158
Selection rate
19.1%
829
Complete population represented in the source disclosure.
158
Records meeting the disclosure's Eligible definition.
19.06%
Eligible records divided by all listed records in the selected scope.
144
Only five privacy-qualified groups are displayed below.
19.1% of the selected scope
80.9% of the selected scope
Age 40+ minus under 40
+2.81 pts
The observed aggregate difference is not statistically clear at the conventional 5% threshold.
A title is displayed only when at least 10 employees are listed and both outcome cells contain at least five employees.
Listed
42
Eligible
10
Ineligible
32
Rate
23.8%
These are descriptive aggregates from one decisional unit. They do not explain individual decisions or provide a legal conclusion.
829 records reconcile to 158 Eligible and 671 Ineligible outcomes.
The published experience contains only aggregates. Exact ages and employee-level rows are excluded.
Aggregate comparisons describe the listed population but do not explain individual decisions or establish a legal conclusion.