Dataplanedataplane
    Medallion Architecture

    Silver and gold layers that actually hold up

    Medallion architecture names the stages but doesn't define what 'cleansed' or 'business-ready' actually mean. Dataplane gives both layers an explicit model to conform to, so silver is genuinely cleansed and gold tables agree across every source.

    The Problem

    A gold layer is only as good as the definition behind it.

    Medallion tells you to land raw, then cleanse, then serve, but never says clean against what, or business-ready in whose terms. With no shared definition, each pipeline answers for itself.

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    Silver cleansing becomes performative. With no shared definition to clean toward, each pipeline scrubs data without a clear goal.

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    Gold proliferates per consumer. Every team hand-models its own business-ready tables, so the same entity ends up shaped a dozen ways.

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    Horizontal collaboration never arrives. Each pipeline refines its own slice in isolation, so the layers leave teams as siloed as they started.

    Dataplane Approach

    From named stages to layers a model defines.

    01

    Make the model explicit

    Lift your entities, relationships, and rules into one central ontology that defines what cleansed and business-ready actually mean.

    extract · model · define
    02

    Conform silver to it

    Cleansing, deduplication, and entity resolution resolve to the model's definitions instead of each pipeline's assumptions.

    bind · cleanse · resolve
    03

    Project gold from it

    Business-ready tables derive from the model as governed views, so every gold table agrees by construction.

    project · govern · conform
    Built on:Data OntologyData QualityData HealingData Lineage

    Outcomes

    Where You Feel It

    A model behind the layers changes what silver and gold can be trusted to do.

    Trust

    Cleansing aims at a shared definition, so cleansed actually means cleansed at every layer.

    Consistency

    Gold tables derive from one model, so business-ready data agrees across sources.

    Cross-team reuse

    Teams build on shared gold instead of re-deriving the same entity per consumer.

    Time to onboard

    A new source or consumer conforms to the model instead of getting its own bronze-to-gold chain.

    Benchmark your medallion layers on a real model.

    We'll make the model explicit for a slice of your data, design your silver and gold layers around it.