/platform/data-tables) is the workspace for comparable metric extraction across a watchlist. You write one prompt describing the metrics you want, and the platform runs it against every entity, normalising the results into a sortable, filterable matrix.
When to use Data Tables vs other surfaces
The difference from Deep Dive is the shape of the interaction: Deep Dive is a conversation about a single obligor where you ask follow-ups and refine the answer; Data Tables is a one-shot extraction across the entire watchlist.
The workspace
There’s one workspace per prompt. The sidebar lists every prompt you’ve authored. The main area has three sections:- Prompt panel: the prompt body. Editable inline.
-
Matrix: rows (typically entities) × columns (typically fiscal years or another comparable dimension). Every value is traceable: click a cell for its reference, source document, pages, and notes, or click an entity name to open a panel with two tabs:
- Documents: the source filings used for that entity.
- Notes: caveats, ambiguities, methodology, and restatements flagged during extraction, with links to the cited pages.
- Views and filters: switch between the three views and filter by entity, status, value type, period, and audit status.
Preview, then apply
Data Tables has a built-in two-step extraction flow:1
Preview on a few CUSIPs
Click Preview. The platform runs the prompt against a handful of sample CUSIPs from the watchlist so you can check it extracts what you expect, without touching the full list.
2
Tune the prompt
Adjust the prompt body until the preview cells look right. Previews are cheap and only cover the sample CUSIPs.
3
Apply to the full watchlist
Once the prompt is dialled in, apply it to the full watchlist. Extraction runs across every entity and the matrix populates as cells come back.
Options
Alongside the prompt, a few choices control what the extraction runs over:Views
The same extracted cells can be sliced three ways. Switch between them from the toolbar:Tips
- Be explicit about units and time bases. “Revenue in USD millions” and “Fiscal year ending June 30” beat “operating revenue” for sortable comparability.
- Pin sector idiosyncrasies in the prompt. For example, exclude entrance fees from DSCR for charter schools, or specify GASB vs FASB.
- Reuse existing prompts with
@. While writing the prompt, type @ to search your prompt templates and embed a reference to one, so you can build on prompts you’ve already tuned instead of rewriting them.
See also
- Prompt Templates → Writing better prompts: how to write prompts that extract clean, comparable values.
- Watchlists: the groups of entities a Data Table runs across.
- Surveillance: the event feed for new disclosures on those same watchlists.