FactVerse Scout
FactVerse Scout helps operations, data, and engineering teams answer three practical questions:
- Does an application have the data it needs?
- If not, which signal, asset, definition, or approval is missing?
- After a gap is resolved, is the application actually using the approved data?
Scout is part of DFS Pro. It turns a data-readiness investigation into a shared, reviewable workflow instead of a spreadsheet, chat thread, or one-off integration script.
What You Can Achieve
- assess readiness for Predictive Maintenance and other data-driven applications;
- see coverage and data gaps for a selected plant, system, or equipment group;
- connect a governed source signal to the correct asset attribute;
- assign decisions to data owners and an approver/deployment owner;
- apply an approved data binding through DFS governance without losing its review history;
- verify that the target application received and used the expected data;
- distinguish customer data, demonstration data, and unverified data clearly.
When to Use Scout
Use Scout when a team is onboarding an application, adding equipment or signals, resolving a model data gap, replacing a source, or reviewing whether an existing integration is still trustworthy.
Scout is not a data-cleaning tool and does not guess the meaning of an unknown signal. Source access, asset definitions, application requirements, and business approval still belong to their accountable owners.
The Customer Journey
| Step | Customer question | Result |
|---|---|---|
| Create an investigation | What application, site, and equipment are in scope? | A named Mission with an owner and a clear boundary |
| Review readiness | What is ready, missing, uncertain, or blocked? | A coverage view with actionable gaps |
| Match data | Which governed signal represents the required asset attribute? | A reviewable binding proposal |
| Validate and apply | Do samples pass validation, and may DFS apply the approved change? | An approved, governed DFS binding change |
| Verify use | Did the application receive and consume the approved data? | A readiness result tied to the same Mission |
Who Does What
| Role | Typical responsibility |
|---|---|
| Mission owner | Defines the business objective, scope, and completion criteria |
| Data operator | Investigates gaps and proposes source-to-asset matches |
| Data steward or domain reviewer | Confirms identity, meaning, units, and provenance |
| Approver / deployment owner | Approves validated evidence, applies the DFS change, and verifies operation |
| Tenant administrator | Enables Scout and assigns access |
One person may hold several roles in a small team, but semantic review and approval responsibilities should remain explicit.
What Scout Proves
Scout preserves the evidence used for each decision. It also records whether that evidence comes from an approved customer source, a demonstration environment, or an unverified source. A successful workflow proves that the reviewed chain works for its stated scope; it does not turn demonstration data into customer acceptance.