Modernise legacy data platforms,
without the big-bang risk.
We modernise legacy databases, ETL and on-premise data warehouses onto Microsoft Azure, AWS, Databricks, Snowflake and Microsoft Fabric - turning complex data transformation into a practical path forward for organisations across Australia.
Your cloud migration may be working.
Your data platform may not be.
Moving servers and applications to Azure or AWS is visible. What's happening underneath is often a different story - and it's where many transformation programs get stuck.
"A cloud platform without a modern data foundation can simply become legacy architecture running in the cloud."
Legacy databases
Core systems still run on databases built 10, 15 or 20+ years ago.
Legacy ETL
Pipelines still depend on yesterday's architecture and tools.
On-premise data warehouses
Warehouses keep running on-premise long after the cloud move.
Point-to-point integrations
Fragile, tightly coupled integrations that get harder to change.
Outdated BI
Reporting platforms struggle with growing data volumes.
Rising costs
Cloud and maintenance costs grow without proportional value.
The goal isn't just to migrate. The goal is to modernise.
Modernisation across the
whole data platform.
From the warehouse and pipelines to integration and BI - so the data platform modernises along with the rest of your cloud transformation.
Legacy Data Warehouse Modernisation
Move on-premise data warehouses to a modern cloud data platform, re-modelled for today's workloads rather than copied as-is.
Cloud Data Migration - Azure & AWS
Migrate data platforms to Microsoft Azure or AWS with phased cut-overs, parallel running and validated, reconciled data.
ETL & Pipeline Re-engineering
Re-engineer legacy ETL jobs into modern, observable pipelines - preserving years of embedded business rules.
Databricks & Lakehouse
Design and build Databricks Lakehouse architectures that unify data engineering, analytics and machine learning.
Snowflake
Modernise onto Snowflake for elastic, governed analytics with clear cost control.
Microsoft Fabric & Azure Synapse
Modernise on the Microsoft data stack with Fabric, Synapse, Data Factory and Power BI working together.
Integration Modernisation
Replace point-to-point integrations with API-led, maintainable integration across a fragmented data ecosystem.
BI & Analytics Modernisation
Move legacy reporting to modern analytics and BI that scales with your data and your users.
Assess. Prepare. Build.
Deploy. Evolve.
Modernise the right things, in the right way, at the right time - in manageable phases that keep the business running.
Assess
Understand the current landscape - systems, dependencies, hidden business rules - and define what success looks like.
Prepare
Build a realistic roadmap and target architecture, and address data quality and governance early.
Build
Build the modern platform and pipelines in manageable phases, not one big-bang release.
Deploy
Cut over with parallel running and data validation, so the business keeps operating throughout.
Evolve
Optimise cost and performance, then unlock analytics and AI on a trusted foundation.
Modernisation doesn't mean
replacing everything.
A better approach is to understand the current landscape, identify what is creating the most business and technology risk, and modernise in stages. These are the paths we deliver most often.
Talk to Us →Rarely a technology problem.
Here's how we avoid the traps.
Going live on time is not the same as delivering business value. These are the most common reasons legacy modernisation programs struggle - and how we address each one.
✓We start with the business outcome and define what success looks like before choosing technology.
✓The platform is a means to an end - we keep the focus on the business problem being solved.
✓Thorough discovery uncovers years of integrations and business rules before migration begins.
✓We modernise in manageable phases, reducing risk, disruption and resistance.
✓Data quality, governance and reconciliation are addressed early, not discovered late.
✓We involve the right stakeholders so changes to processes and people are planned, not imposed.
Where we
modernise to.
Common questions
What is legacy data modernisation?
It is the process of moving data platforms built on older technology - on-premise databases, data warehouses, ETL tools and reporting - to a modern cloud data platform, re-engineered so it is scalable, governed and ready for analytics and AI.
Our applications are already in the cloud. Why is our data platform still a problem?
Moving servers and applications is only part of the transformation. If legacy databases, ETL and on-premise warehouses stay behind, costs rise and value stalls. A cloud platform without a modern data foundation can simply become legacy architecture running in the cloud.
Which platforms do you work with?
We modernise onto Microsoft Azure (including Microsoft Fabric, Azure Synapse Analytics and Azure Data Factory), AWS, Databricks and Snowflake, with Power BI for analytics.
Do you migrate everything in one go?
No. Big-bang migrations are one of the most common reasons modernisation fails. We modernise in manageable phases with parallel running and data validation, so the business keeps operating throughout.
How do we get started?
Book a free modernisation assessment. We review your current data landscape, the business outcomes you need, and outline a practical, phased path forward.