Multi-unit Data Foundation system blueprint

This system connects location-level operational sources to a governed model for sites, products, people, customers and periods. It validates freshness, completeness and conformance so every downstream multi-unit workflow uses comparable data without replacing the source systems.

Business function
Operations
Operating context
Multi-unit operators
Primary owner
Head of Data

What starts the system

A source-data change, scheduled pipeline run or approved definition update.

Human boundary

Definition and hierarchy changes follow named owner approval and version control.

How the system works

  1. 1. Ingest source records with lineage and map them to governed shared entities.

  2. 2. Validate freshness, completeness, uniqueness and cross-site comparability.

  3. 3. Publish approved data products, definitions and quality exceptions to downstream owners.

Inputs

  • Source-system schemas and location identifiers
  • Business definitions, hierarchies and calendars
  • Data ownership, access and quality requirements

Outputs

  • Governed multi-unit data products and definitions
  • Data-quality, lineage and ownership register

Controls

  • Definition and hierarchy changes follow named owner approval and version control.
  • Role-based access limits sensitive location, employee and customer data.

Examples of systems it may connect to

  • Microsoft Fabric
  • Snowflake
  • Databricks
  • dbt
  • Qlik Sense

What can carry across companies

The reusable core is source onboarding, entity resolution, quality testing, lineage and governed publication.

What must be adapted

Each estate supplies its source landscape, site hierarchy, local identifiers, calendars and access policies.

Start with the closest pattern–or start from your process.

The catalogue represents reusable operating shapes, not fixed off-the-shelf applications.

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