Cloud Migration & Modernization
Retire aging on-premise systems without putting live operations at risk.
Outdated on-premise databases and warehouses slow down innovation and drive up maintenance costs. A structured migration to Azure, Databricks or Fabric modernizes the infrastructure step by step with low risk, while existing processes keep running uninterrupted during the transition.
- Lower ongoing infrastructure costs.
- Better scalability as data volume grows.
- Less effort spent on maintenance and patching.
infrastructure cost
scalability under peak load
to full migration
maintenance effort
Calculated by comparing total cost of ownership before and after migration.
- 01
System landscape assessment
We assess existing systems by migration effort and risk.
- 02
Target architecture
We define the cloud target environment and migration sequence.
- 03
Pilot migration
We migrate a non-critical system as a test run.
- 04
Phased migration
We move further systems in controlled waves.
- 05
Decommission & optimization
We decommission legacy systems and optimize the new environment.
Steps
Data sources
Stakeholders
From first data access to production – every step delivers a tangible interim result.
Database schemas
Structure and scope of existing on-premise databases.
ETL jobs
Existing transformation logic and schedules.
Access logs
Usage patterns to prioritize migration.
License and cost data
Existing license and operating costs as a baseline.
Dependencies
Connections to downstream applications and reports.
Compliance requirements
Requirements around data residency and security standards.
IT leadership
Predictable migration with clearly calculated risk.
Finance
Transparent cost development instead of hidden maintenance cost.
Business units
No interruption of running processes during migration.
Executive management
A future-proof infrastructure as a basis for growth.
Lower ongoing infrastructure costs.
Better scalability as data volume grows.
Less effort spent on maintenance and patching.
Faster access to modern analytics and AI services.
Higher resilience through cloud-native architecture.
With a solid data foundation this use case gets faster, cheaper and far more stable.
A clear target picture of the data platform reduces migration risk.
Existing automation speeds up repeated migration steps.
Standardized security concepts simplify cloud connectivity.
Established governance eases migration of sensitive data.
Lakehouse architecture
Migration is the ideal moment to build a lakehouse.
Cost optimization (FinOps)
Migration and cost optimization are planned together from the start.
Data governance & permissions
Migration offers the chance to set up governance cleanly from scratch.
Lakehouse Architecture
A central lakehouse replaces the patchwork of data warehouse, data lake and Excel exports.
Data Integration from ERP & MES
Automatically merge ERP and MES data instead of exporting and reconciling manually.
Streaming & Real-Time Data
Instead of daily batch runs, relevant metrics are available within seconds.