Data Visibility

Centralize and standardize trusted data so dashboards, reports, and data-driven systems share one coherent source of truth.

Why this exists

AetherDev systems only stay reliable when truth remains consistent from ingestion to interface. When the same concepts exist as multiple extracts, multiple definitions, and multiple dashboard implementations, we get conflicting numbers, brittle downstream dependencies, and repeated manual reconciliation.

March 2026 Registry Reconciliation

The updated BOUSD registry materially sharpened the Data Visibility workstream in three ways:

the BOUSD reporting extracts are now documented as a single production family instead of isolated repo notes;
the Perpetual Data Reports Portal is tied more explicitly to live report families such as attendance, PADC, enrollment planning, and staff-device readiness;
Atlas now carries the unresolved gaps that most affect trust: missing report ownership inventory, incomplete sheet and host maps, and manual-versus-scheduled refresh ambiguity on some legacy dashboards.

Measures of success

Canonical datasets exist with clear ownership, stable schemas, and published refresh expectations.
Key KPIs have a single definition and are reused consistently across dashboards and reports.
Freshness and data quality checks are visible, and failures have clear remediation paths.
Teams can self-serve trusted reporting without repeated manual pulls or bespoke extracts.
Access controls and privacy constraints are enforced by design.

Active projects

Key risks

Metric definition drift between dashboards, portals, and report consumers.
Missing family-level documentation for shared extract jobs and their sheet contracts.
Report ownership gaps reduce trust and push teams back toward ad hoc pulls.
Manual-versus-scheduled refresh ambiguity persists on some long-lived Google Workspace reporting surfaces.
Privacy and access controls drift as reporting surfaces expand.