Data and AI Consultancy
— DATA MODERNISATION
Your data infrastructure shouldn't be the reason your business can't scale.
We modernise legacy data environments from on-premise to cloud, from fragmented to unified without taking the business offline.
The Problem
Many mid-market businesses are running SQL Server instances on ageing hardware, with a
reporting layer that was built five years ago for a business half the current size. Adding new data sources requires a developer. Running new reports takes hours. And the whole thing is
maintained by one person who's been there for eight years. This is a modernisation problem. And it compounds over time.
What We Do
01
Legacy Data Platform Assessment
We audit your current architecture: what you have, what it's costing you, where the risks are, and what modernisation would deliver.
02
Cloud Migration (Azure / Microsoft Fabric)
We lift your data from on-premise infrastructure to a modern cloud platform, with a migration plan that minimises downtime and risk.
03
Data Warehouse Modernisation
Rebuilding legacy data warehouse architectures on modern platforms — lakehouse, medallion architecture, or semantic model — depending on what your business needs.
04
ERP Data Integration
Connecting your new or existing ERP (SAP, Dynamics 365, NetSuite) to a modern analytics layer so your operational data flows into reporting automatically.
05
Reporting Layer Migration
Moving from legacy tools (SSRS, Crystal Reports, Excelbased packs) to Power BI with a properly structured semantic model underneath.
Our Modernisation Approach
We don't rip and replace. We modernise in stages: assess, prioritise, migrate, validate, decommission. Each stage delivers something the business can use before the next one starts.
Assess
Prioritise
Migrate
Validate
Decommission
Stack
Azure Data Lake
Microsoft Fabric
Azure Synapse Analytics
DBT
Power BI
SQL Server
Azure Data Factory
Typical Engagement
Delivery Model
Pricing
12-24 weeks
Phased stages
Fixed price per phase available