Cloud Data Migration & Modernisation

Data Migration

Operational efficiency

Automated pipelines reduce migration time and eliminate manual intervention.

Data reliability

Every dataset is validated, versioned, and verified throughout the migration process.

Scalable environment

Data lands in an environment designed to grow with your workloads and use cases.

Governed operations

Full lineage, compliance, and encryption ensure robust security from end to end.

Faster Decisions

Lower
Costs

Improved Accuracy

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Step 1

Assess and Plan
We evaluate existing data sources, formats, and dependencies to define a migration strategy.

Step 2

Clean and Prepare
We standardise schemas, remove duplication, and validate integrity before transfer.

Step 3

Transfer and Transform
We migrate your data to the optimal environment for your workloads or chosen stack.

Step 4

Validate and Secure
We verify accuracy, completeness, and access controls to meet compliance and quality standards.

Step 5

Monitor and Scale
We automate updates, monitoring, and reporting for continuous, secure data movement.

Platforms

Azure

AWS

Google Cloud

Frameworks

Snowflake

LangChain

Hugging Face

Tensorflow

Databases

Snowflake

Supabase

Databricks

Monitoring

PowerBI

Streamlit

Dataiku

Frequently Asked Questions

What types of data can you migrate?

We handle structured, semi-structured, and unstructured data, from databases to files, logs, and documents.

Do you support hybrid or on-prem environments?

Yes, we design migration paths for hybrid, on-prem, and multi-cloud architectures.

How do you ensure data integrity?

We use validation checkpoints, checksum verification, and monitoring to ensure data lands complete and consistent.

Is there downtime during migration?

Minimal to none. Most migrations occur in parallel, ensuring systems stay live and uninterrupted.

Can you prepare data for AI use after migration?

Absolutely. We structure and classify data so it’s immediately ready for analytics, machine learning, and automation.