> ## Documentation Index
> Fetch the complete documentation index at: https://docs.textql.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Module 5 · Import a Power BI / Tableau Dashboard

> The fastest way off Power BI / Fabric / Tableau isn’t a rewrite — it’s giving Ana what the original dashboard is made of and rebuilding it on governed data. You keep the old too… (~30 min)

The fastest way off Power BI / Fabric / Tableau isn't a rewrite — it's giving Ana what the original dashboard is made of and rebuilding it on governed data. You keep the old tool running and prove parity side-by-side.

## Two ways to bring the dashboard in

<CardGroup cols={2}>
  <Card title="Source file (.pbit / .twb)">Export the template/workbook and upload it. Best when you have the file and want the model, measures, and layout in one shot.</Card>
  <Card title="Live BI connector">Power BI or Tableau is connected as a data source in your workspace. Ana reads the published datasets, measures, and metadata directly — no export needed. Best when the file is locked down, or you want the rebuild to track a report that keeps changing.</Card>
</CardGroup>

<Note>
  **What each path exposes** — A **Power BI template (`.pbit`)** carries the data model, DAX measures, and report layout — Ana reads all three (this replaced the old zip/xlsx/unpack hack). A **Tableau workbook (`.twb`)** is XML: datasource fields, calculated fields, and worksheet/dashboard layout. A **connected Power BI / Tableau source** exposes the published datasets, measures, and field metadata through the connector. Any of them gives Ana the logic to reconstruct the dashboard.
</Note>

<Warning>
  **Add screenshots — this is what nails the look & feel** — Whichever path you use, **attach 2–3 screenshots of the original dashboard** (the full view, plus any key tiles). The file or connector gives Ana the *logic*; the screenshots give her the *look* — layout, color, card styling, chart types. Rebuilds come out far closer to the original when Ana can **see** it, not just read its model. This is the single highest-leverage thing you can hand her.
</Warning>

* **Give Ana the source + screenshots.** Path A: upload the `.pbit` / `.twb`. Path B: point her at the connected Power BI / Tableau source. Either way, attach 2–3 screenshots of the original and ask her to read the model, measures, and layout before building anything.
* **Map measures → governed metrics.** Bind each visual to an ontology metric instead of re-implementing DAX/Tableau calcs ad hoc — that's what makes the number deterministic and auditable. Any measure with no clean mapping gets flagged, not guessed.
* **Build a static-first snapshot** for the visuals actually shown (Module 6 is the how + why).
* **Replicate the layout** — tiles, filters, trend — against the snapshot.
* **Reconcile figure-for-figure** to the source dashboard before you trust it.

```text Prompt theme={null}
Here's a [Power BI .pbit / Tableau .twb] dashboard, plus screenshots of how it looks today. Read its data model, its measures, and its layout — and study the screenshots for the look and feel — don't build yet. Then: (1) list every measure and map each to a governed ontology metric, flagging any that don't map cleanly; (2) propose the equivalent data-app layout (cards, trend, breakdown, filters) matching the screenshots; (3) tell me which source tables/joins each metric needs. Show me the plan before you build.
```

```text Prompt theme={null}
Power BI / Tableau is connected as a data source in this workspace. Read the published dataset and its measures for the [dashboard/report name] directly through the connector — and here are screenshots of how it looks today. Same plan: map each measure to a governed ontology metric (flag any that don't map), propose the matching data-app layout from the screenshots, and tell me which underlying tables/joins each metric needs. Show me the plan before you build.
```

<Check>
  **You'll see:** a measure-by-measure mapping (source measure → ontology metric), a layout proposal that mirrors the original's look from your screenshots, and a flagged list of anything that needs a definition before it can be rebuilt faithfully.
</Check>

```text Prompt theme={null}
Now build it, then reconcile: reproduce the source dashboard's default (unfiltered) headline numbers exactly, and pick one filtered slice and match it to the dollar against a fresh query on the warehouse. Show me both dashboards' numbers side by side and call out any difference and why.
```

<Check>
  **You'll see:** the rebuilt app with its numbers lined up against the source — matching figures where the logic is faithful, and an explicit note on any intentional difference.
</Check>

<Warning>
  **Keep the old tool running** — Don't cut over on faith. Run the data app **alongside** the Power BI / Tableau original until the numbers reconcile and the team trusts it. For estate-wide migration (inventory, semantic-layer translation, cutover, adoption), the [Migrate from Your BI Tool](/workshops/bi-migration/overview) workshop is the bigger playbook — this module is the single-dashboard hands-on.
</Warning>

<Accordion title="What usually doesn't come across cleanly">
  Visual-level DAX with no governed equivalent, report-only calculated columns, custom visuals/plugins, and pixel-exact formatting. Rebuild the **logic** as governed metrics and the **intent** of the layout — not every cosmetic detail. Flag anything you can't map rather than approximating a number.
</Accordion>

### ✅ Checkpoint

* [ ] You gave Ana the source (file or connected) *and* screenshots of the original
* [ ] The app reproduces the source dashboard's headline numbers to the dollar
* [ ] Every source measure maps to a governed metric (or the unmapped ones are flagged)
* [ ] The app runs alongside the original for parity testing