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Medallion lakehouse on Databricks or Snowflake

A bronze, silver and gold lakehouse that turns raw data from every system into trusted, analytics-ready and AI-ready data products.

Solution blueprint · Data modernization

The challenge

Data arrives from ERP, CRM, SaaS tools and devices in different shapes and at different speeds. Reports disagree, data scientists spend most of their time cleaning, and nobody can trace where a number came from.

Our approach

We land everything as-is in a bronze layer, clean and conform it in silver, and publish business-ready gold tables for BI, machine learning and generative AI. Governance, lineage and quality checks run across every layer.

Architecture

How the pieces fit together. Scroll sideways on small screens.

SourcesERP and financeCRM and salesSaaS applicationsIoT and eventsFiles and documentsIngestAuto Loader / SnowpipeCDC from databasesKafka streamsAPI connectorsBronzeRaw, as receivedFull history keptSchema capturedReplayableSilverCleaned and typedDeduplicatedConformed keysQuality rules appliedGoldBusiness aggregatesKPIs and metricsML feature tablesData productsConsumePower BI / TableauML modelsGenAI and RAGData sharingGovernance: Unity Catalog or Snowflake Horizon — access control, lineage, data qualityOrchestration and CI/CD: Workflows, Airflow, dbt, Git-based deployments

Key components

  • Databricks with Delta Lake and Unity Catalog, or Snowflake with Snowpipe and Horizon
  • Auto Loader, Snowpipe and change data capture for ingestion
  • dbt or Delta Live Tables for transformations
  • Data quality rules and expectations between layers
  • Workflows or Airflow for orchestration with Git-based CI/CD

What you can expect

  • One governed source of truth for reporting and AI
  • Full history kept in bronze, so any layer can be rebuilt
  • Clear lineage from dashboard back to source
  • Lower cost through separated storage and compute

How we deliver it

  1. Assess

    Review current systems, data and goals, and agree success measures.

  2. Design

    Target architecture, security model, plan and fixed quote.

  3. Build and test

    Agile sprints with demos, automated tests and documentation.

  4. Launch and support

    Production rollout, knowledge transfer and optional managed support.

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