Provider and public-record normalization

Provider and public-record data changes across portals, spreadsheets, registries, and scraped sources before teams can rely on it.

Mage

I mapped this healthcare use case as a Mage workflow.

  • ingest government portals, registries, CSV and Excel files, and scraped datasets
  • validate schemas, malformed rows, field mappings, and source changes
  • resolve provider entities and generate diff reports
  • publish reference graphs, quality metrics, and source-backed context

You can inspect source changes, schema decisions, entity matches, diffs, reference graph updates, and delivery state before analysts or applications use the provider data.

Use Mage to normalize provider and public-record data into traceable reference graphs.

Provider and public-record data changes across portals, spreadsheets, registries, and scraped sources before teams can rely on it.

Government portals, CSV and Excel files, registries, and scraped datasets flow into Mage dynamic blocks for schema validation, entity resolution, diff reports, and provider reference graphs.

From healthcare source chaos to governed action

Use Mage as the execution layer between the specific sources, validation rules, governed delivery targets, and reusable context this healthcare workflow needs.

Move Stripe customer data into BigQuery every weekday before 8am.

Map public sources. Pull portals, registries, CSV and Excel files, scraped datasets, and public records into one normalization workflow.

Why did revenue freshness drop?

The Stripe ingest arrived 42 minutes late, delaying the customer revenue model.

Stripe ingest delayed 42 min

Validate provider records. Check schemas, field mappings, source completeness, malformed rows, deduplication, and entity resolution quality.

Customer syncRun delayed
Inspect run
Late source foundRetry availableOpen logs

Register source evidence. Version source URLs, schema decisions, entity matches, validation results, diffs, and graph updates as reusable context.

Pipeline
Table
Chart
File
AnswerRevenue freshness dropped after the Stripe ingest arrived late.

Deliver reference outputs. Publish diff reports, provider reference graphs, lookup tables, quality metrics, and analyst-ready change summaries.

How Mage normalizes provider and public-record data

Mage turns changing public healthcare records into validated provider references, diffs, and reusable graphs.

Run the provider normalization workflow. Pull the portal, registry, CSV, Excel, and scraped sources, validate schema changes, resolve entities, publish diffs, and preserve the source evidence.

The provider normalization workflow is ready to review. I ingested the public sources, validated schema changes, resolved provider entities, generated diffs, and published the reference graph.

Output comparisonWithin tolerance
Current modelModernized workflow

99.8% matched · Monthly revenue, ARR, and accounts checked

Start with the public source. Start with the portal, registry, spreadsheet, scrape, or public-record refresh that keeps changing shape.

Ingest public records. Mage ingests government portals, CSV and Excel files, registries, and scraped datasets into inspectable dynamic blocks.

Validate source changes. Validate schemas, field mappings, source completeness, malformed rows, and source-change signals before entity resolution.

Resolve entities. Resolve providers, facilities, licenses, and public-record entities into a reference graph teams can trust.

Publish reference outputs. Publish diff reports, provider reference graphs, lookup tables, quality metrics, and analyst-ready change summaries.

Keep source evidence. Record source URLs, schema decisions, entity matches, validation results, diffs, and downstream delivery state.

What the workflow includes

Coordinate changing sources Mage pulls government portals, registries, CSV and Excel files, scraped datasets, and public records into dynamic blocks that make source changes visible.

Resolve provider identity Schema checks, type coercion, entity matching, deduplication, and change detection run before provider records become reference data.

Publish traceable references Diff reports, provider reference graphs, quality metrics, and downstream lookup tables stay tied to the sources and validation rules that produced them.

Use case details

The workflow view shows sources on the left, Mage execution in the middle, and governed outputs plus AI context on the right.

Business problem

Provider and public-record data changes across portals, spreadsheets, registries, and scraped sources before teams can rely on it.

Mage workflow story

Normalize portals, registries, CSV and Excel files, scraped datasets, schema validation, entity resolution, diff reports, and provider reference graphs.

Workflow diagram

Government portals, CSV and Excel files, registries, and scraped datasets flow into Mage dynamic blocks for schema validation, entity resolution, diff reports, and provider reference graphs.

Bring Mage the government portals, registries, CSVs, Excel files, and scraped datasets that keep changing. Mage will map schema validation, entity resolution, diff reporting, and provider reference graph delivery.