One governed lakehouse, not ten silos.
Without a unified foundation, models never reach production.
We consolidate fragmented systems into a lakehouse and modern warehouse, from legacy migrations to real-time pipelines, with quality, security and observability built in.
Lakehouse- Bronze
- Silver
- Gold
- Dashboards
- Models
- Agents
Azure
A production-grade data foundation.
We modernize without rip-and-replace, plugging into the teams and tools you already run and migrating on defensible timelines.
Lakehouse and warehouse architecture
A Delta Lake and Unity Catalog design that handles batch and streaming in one place, with ACID reliability and elastic scale.
Streaming and batch pipelines
Reliable ingestion from every source system, with contracts and tests so data lands clean and on time.
Quality and observability
Monitoring, alerting and freshness checks that catch issues before they reach a dashboard or a model.
Legacy migration and modernization
Move off aging warehouses and on-prem stacks without stalling the roadmap.
The lakehouse we build on Databricks.
One copy of the data, refined in three layers under one governance layer, with a context layer that gives every dashboard, model and agent the company's own facts. It runs in your own account on AWS, Google Cloud or Azure.
- Operational databases
- Files and spreadsheets
- Event streams
In your cloud account- Access policies
- Lineage
- Audit logs
- PII masking
- Data contracts
- BronzeRaw, exactly as it landedKept for replay and audit
- SilverCleaned, conformed, testedData contracts enforce the schema
- GoldBusiness-ready tablesModelled for how the business runs
- Metric definitionsOne definition of revenue, margin and churn
- Business rulesWho may see what, and what counts
- Document searchContracts, filings and notes, indexed for retrieval
- DashboardsDatabricks SQL to Power BI or Tableau
- Models and agentsMachine learning and AI agents that answer from the context layer
- Shared dataDelta Sharing to partners, portfolio companies and apps
Bronze keeps the raw record for replay and audit, Silver cleans and conforms it under tested contracts, Gold models it for how the business runs.
Bronze, silver and gold on Azure Databricks, with quality checks and alerts on each load; 30 analyst hours a week back.
Read the case study
Start from where you are.
Platforms are rebuilt in place, one domain at a time, while the business keeps running on what it has.
- 01Your warehouse works, but it is not enoughWe build the lakehouse beside it and move workloads across one domain at a time.A data lake beside the legacy systems; first-pass valuations went from 3 to 5 days to under 1 hour.Colliers
- 02Batch is too slow for the businessWe stream changes as they happen, with change data capture from your databases.Price and availability changes propagate in under a second, with 10x the pipeline throughput.Booking.com
- 03Every system tells a different storyWe audit every source first, rank the use cases by value, then build one governed copy.A two-month audit, then one governed copy on Azure Databricks; investor report prep fell 55%.Bridge Investment Group
Platform work can pay for itself.
Consolidated pipelines and right-sized compute show up on the cloud bill. From our case studies:
Governance: catalog, lineage, access.
Centralized metadata, fine-grained access and full lineage, to stay compliant across your data and AI estate.
Unity Catalog rollout
Centralized access, lineage and policy across the estate.
Data contracts
Enforce schemas so producers and consumers stay in sync.
Lineage from the start
Missing lineage and access control turn compliance into a fire drill; we build both in from the first pipeline.
- Real Estate & Construction55%less time producing investor reportsBridge Investment Group cut investor report prep by 55%
- CPG31%lower monthly cloud costNu Skin cut monthly cloud costs 31% by rebuilding its data pipelines
- Operations10xmore data pipeline throughputBooking.com moved pricing and inventory data from batch to sub-second
Common questions.
What does a data platform engagement include?
We consolidate fragmented systems into a lakehouse and modern warehouse, from legacy migrations to real-time pipelines, with quality, security and observability built in. The work covers four things: lakehouse and warehouse architecture, streaming and batch pipelines, quality and observability, and legacy migration and modernization.
Do we have to replace our existing data warehouse?
No. We build the lakehouse beside it and move workloads across one domain at a time. For Colliers we built a data lake beside the legacy systems instead of replacing them, and first-pass valuations went from 3 to 5 days to under 1 hour.
How long does a data platform migration take?
It depends on how many sources and how much history you carry. From our case studies: Bridge Investment Group started with a two-month audit of every source system, EVERFI's move to Snowflake ran 32 weeks with a parallel run before cutover, and Booking.com's streaming rebuild was a 40-week engagement.
Do Databricks and Snowflake work together?
Yes. Many companies run both: Databricks for pipelines, machine learning and agents, Snowflake for SQL analytics. We build on Databricks and connect to Snowflake when it is already in place, as for Colliers, where Snowflake serves valuation and financial data marts to Power BI from the governed data lake.
How does Blue Orange handle data governance?
With centralized metadata, fine-grained access and full lineage, to stay compliant across your data and AI estate. That means a Unity Catalog rollout for centralized access, lineage and policy; data contracts that enforce schemas so producers and consumers stay in sync; and lineage built in from the first pipeline, not added after.
What has Blue Orange built on a data platform?
Booking.com moved pricing and inventory data from batch to sub-second, with 10x more pipeline throughput, through a change data capture pipeline into Snowflake. Nu Skin cut monthly cloud costs 31% by consolidating 150+ pipelines into 40. Bridge Investment Group cut investor report prep by 55% after an audit of every source system.