# Desk log AIDB-OPS-VS-BI-20260822

**Status:** First-party sanitized composite/demo; not raw, customer, source, benchmark, or third-party data.
**Page:** https://infinisynapse.com/en/blog/operational-dashboard-vs-bi-dashboard
**Run ID:** `AIDB-OPS-VS-BI-20260822`
**Date:** 2026-08-22 (Saturday)
**Operator:** InfiniSynapse Data Team
**Attestor:** William Zhu, InfiniSynapse cofounder ([GitHub @allwefantasy](https://github.com/allwefantasy))
**Contact for contradictions:** zhuhl@infinisynapse.com

## What this file is

A downloadable record of a one-queue path (open a BI ticket for a “miss” tile) versus keeping the certified contribution tile published and generating a Wednesday pack. Companions: [aggregate CSV](https://infinisynapse.com/blog-media/operational-dashboard-vs-bi-dashboard/downloads/aggregate-AIDB-OPS-VS-BI-20260822.csv) and [verify script](https://infinisynapse.com/blog-media/operational-dashboard-vs-bi-dashboard/downloads/verify-AIDB-OPS-VS-BI-20260822.py). It is **not** a named-logo customer case, a vendor bake-off, or an RFC 4180 / Arrow / Gartner experiment.

## Six-step disclosure method

1. Write which tiles stay in BI and which questions are weekly packs.
2. Leave the certified close tile published.
3. Generate the ops pack on authorized sources.
4. Rerun the same goal next Wednesday. Confirm the certified tile is untouched.

## Source and goal

| Field | Value |
|---|---|
| Published object | Finance-owned contribution tile (certified grain) |
| Ops sources | Read-only Postgres replica + sanitized SKU note |
| Contrast | One queue for both jobs vs ops ask + keep BI grain |

## Results

| Retrieval state | Backlog tickets | Wednesday pack files | Certified tile published |
|---|---|---|---|
| One queue for both jobs | 1 | 0 | 1 |
| Ops ask + keep BI grain | 0 | 4 | 1 |

Wall-clock for the successful ops run: 22 minutes (warehouse time excluded).

## What you may cite

- Artifact counts 1/0/1 → 0/4/1, ~22 min wall-clock, run ID

## What you may not claim

- Customer speedup %, a 40% faster backlog, official EEAT score, named-logo case, or that IETF / Arrow / Gartner / WAIC scored this run

## External context (not validation of this run)

- [Sarikaya et al. dashboard design space](https://doi.org/10.1109/TVCG.2018.2864903) (retrieved 2026-08-29)
- [Yigitbasioglu and Velcu dashboard review](https://doi.org/10.1016/j.accinf.2011.08.002) (retrieved 2026-08-29)
- [Power BI semantic models](https://learn.microsoft.com/en-us/power-bi/connect-data/service-datasets-understand) (retrieved 2026-08-29)
- [Looker semantic modeling](https://cloud.google.com/looker/docs/what-is-lookml) (retrieved 2026-08-29)
- [Grafana dashboards](https://grafana.com/docs/grafana/latest/dashboards/) (retrieved 2026-08-29)
- First-party homepage recognition only: [2026 WAIC Future Tech OPC Excellence Award](https://infinisynapse.com/#recognition)

## Validation boundary

No independent third-party, media, or customer reproduction was known as of 2026-08-29. Reproduction requires the full source, semantic, query, run, artifact, review, retention, timing, and conflict-of-interest disclosures described in the article.