From Legacy Warehouse to Modern Lakehouse - Designed for Cost.
Replatform Teradata, Netezza, Exadata, and on-prem Hadoop into Databricks, Snowflake, Microsoft Fabric, or BigQuery. We design for performance, but cost stays the headline.
Why Modernise the Data Platform?
Legacy warehouses are slow, expensive, and increasingly out of step with how modern analytics, AI, and ML actually work. The modern lakehouse separates storage from compute, supports both BI and ML workloads, and – done right – costs less than what you are running today.
We replatform with a financial model in week one and FinOps controls live by week four. The CFO is in the room before the cutover plan is signed.
Our Six-Stage Modernisation Method
Estate discovery
Inventory of workloads, owners, dependencies, and current cost
Two target-state architectures with cost models
Migration plan
Workload-by-workload sequencing with downside risk mapped
Build & migrate
Medallion (bronze / silver / gold) layouts with data contracts
Row-count, query-result, and performance parity sign-off.
Decommission
Phased retirement of legacy with rollback path live until day-90
FinOps - Cost Stops Being a Surprise
The most common reason cloud data programmes go over budget is a missing FinOps layer. We build it in.
- Tagging and chargeback model live before workload one is migrated.
- Query cost monitoring with anomaly alerts to data owners.
- Auto-scaling guardrails and reserved-capacity strategies.
- Monthly cost review with optimisation backlog.
- Unity Catalog / Purview / Collibra integration. Lineage, classification, access from day one.
- Row-level security and column masking. Implemented in metadata, not application code.
- Data contracts. Producer-consumer agreements enforced in CI/CD.
- Audit-ready logging. For SOC 2, GDPR, HIPAA, RBI / SEBI / DPDP.
Every modernization project lives or dies at the cutover. We engineer for safety from day one.
Unity Catalog / Purview / Collibra integration
Lineage, classification, access from day one.
Row-level security and column masking
Implemented in metadata, not application code.
Data contracts
Producer-consumer agreements enforced in CI/CD.
Audit-ready logging
For SOC 2, GDPR, HIPAA, RBI / SEBI / DPDP
Manufacturing
Plant-level data, OEE, energy and emissions reporting
BFSI
Risk, exposure, AML, regulatory reporting estates
Healthcare
EMR, claims, population-health, research data lakes
Retail
Omnichannel transactions, store-ops, customer behaviour
Supply Chain
Multi-system supply data, supplier performance, network design
FAQ
Frequently Asked Questions
How do we know the cloud will actually be cheaper?
You will see the cost model in week one. We baseline current spend (compute, licence, ops, energy where relevant), build the target-state cost model, and walk through assumptions. We do not start migration without a defended cost case.
What about our existing dashboards and reports?
They keep working. We provide a compatibility layer (views, semantic models, virtualisation) during the cutover so downstream consumers do not feel the move.
Can we phase the modernisation?
That is the default. We sequence migration by workload value and risk – usually 6-9 quarterly waves.
Ready to Modernise?
Book a 60-minute architecture review. We will walk through your current estate, identify two viable target architectures, and put rough order-of-magnitude cost numbers on each.