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Data landscape & governance

The EA problem

Data is the asset every other asset moves. But it's the hardest to see: it lives inside applications, flows along integrations, and carries regulatory weight that varies wildly from one entity to the next. The EA questions are: What information do we hold? Where is it stored and where does it flow? How sensitive is it, and what rules apply? Without answers, every change risks a compliance surprise.

How ArcaMira addresses it

The Data lens (Estate → Assets, Data lens, /assets?lens=data): the data-layer entities — data entities, stores, pipelines, and products — catalogued alongside the applications that produce and consume them.

Structured classification on data entities:

  • Sensitivity tier — Public / Internal / Confidential / Restricted.
  • Regulatory flags — PHI, PII, GDPR, CCPA, SOX, FERPA, FedRAMP, ITAR, GovCloud, etc.
  • Data residency, business owner, and data steward — note this layer deliberately distinguishes the functional business owner from the named steward accountable for quality.
  • PII flags and notes.

Lineage and flow. Because data entities are linked to the applications that produce and consume them, you can trace where information originates and where it ends up — and the impact analysis "data at risk" view flags when the applications affected by a change are the only producers of a data feed.

dbt awareness. ArcaMira can import a dbt manifest to bootstrap data-layer entities and lineage from your transformation project, and export a data catalogue for interoperability.

What good looks like

  • Sensitive and regulated data entities classified, with sensitivity tier and regulatory flags set.
  • Each significant data entity has a producing application and known consumers.
  • A data steward named for the entities that carry compliance weight.
  • "What feeds break if we retire this application?" is answerable in a couple of clicks.