Cloud migration consulting that turns legacy data platforms into a cloud-native AI advantage

We design, build and operate cloud data migration solutions that move your analytics, AI and BI workloads from on premise to cloud-native and multi cloud data platforms – safely, fast and with measurable cost savings.

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Cloud migration consulting that turns legacy data platforms into a cloud-native AI advantage

We design, build and operate cloud data migration solutions that move your analytics, AI and BI workloads from on premise to cloud-native and multi cloud data platforms – safely, fast and with measurable cost savings.

Cloud migration consulting that turns legacy data platforms into a cloud-native AI advantage

Is your cloud migration supposed to cut costs and unlock AI, but instead feels risky, slow and impossible to execute without breaking critical reports and operations? Modernizing from on premise to cloud data platforms often stalls because of unclear ownership, underestimated complexity and fear of outages. Teams see overlapping tools, fragile pipelines and compliance concerns, so data migration to the cloud becomes a series of tactical fixes instead of a structured, value-focused transformation.

Who gets the most value from cloud migration

What We Deliver

Cloud data migration factory and automation

We set up a reusable cloud data migration factory that standardizes how you move schemas, pipelines, dashboards and machine learning workloads into cloud native AI platforms.

Cloud agnostic and multi cloud data platform design

Our architects design cloud agnostic data platforms that run on Google Cloud, Azure, AWS or hybrid, using containerization and multi cloud orchestration so you are not locked into a single provider.

From on premise and big data to modern data lakes

We help you migrate traditional on premise data warehouses, Hadoop clusters and bespoke big data platforms into modern, elastic data lakes and lakehouses in the cloud.

Cloud data migration testing and quality-by-design

We build robust cloud data migration testing into your pipelines: automated reconciliation, schema checks, performance benchmarks and data quality rules that run from dev to production.

What We Deliver

Step 1 — Discovery and Scoping

We align business goals, KPIs, priority lines, use cases, and constraints with service, operations, digital, and IT stakeholders.

Step 2 — Data and Telephony Assessment

We review sample data, telephony setup, routing logic, and system dependencies to identify the best first use case.

Step 3 — Design and Build MVP (6-8 weeks to first outcome)

We design conversation flows, implement integrations, configure guardrails, and launch the first production use case.

Step 4 — Adoption and Scale

We optimize real data and expand to more lines, markets, and languages.

How Collaboration Looks in Practice

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What our clients say

"DS STREAM's collaborative and innovative approach made our platform resilient and scalable, enabling us to support millions of users as we grow. Their thorough research and strategic kickoff made a significant impact."

Adam Murray

Head of Product Development, Sportside

"DS STREAM significantly improved the efficiency of our category management processes and enhanced the precision of our business decisions. Their innovative analytical ideas delivered measurable sales growth and a competitive edge."

Sandra Lemańska

Category Manager, Lorenz Polska

Selected Clients

Book a 30-minute consultation about your cloud migration

CONTACT US

Business Impact

Business Impact of Migration to Cloud

Infrastructure cost reduction

30–50% infrastructure cost reduction over 3 years by decommissioning on premise data centers and rightsizing cloud compute and storage.

Faster delivery of analytics and AI

2–3x faster delivery of new analytics and AI use cases thanks to standardized data migration on cloud, reusable patterns and automated testing.

Fewer incidents on reporting and data pipelines

40–60% fewer incidents on reporting and data pipelines after migration, due to built-in quality checks, observability and clear ownership.

Faster region and acquisition integration

Weeks instead of months to roll out cloud to cloud data migration for new regions or acquisitions, accelerating integration and time-to-value.

Higher data adoption across business units

Measurably higher data adoption across business units as users gain a single, trusted multi cloud data platform instead of fragmented legacy systems.

Drop us a line and check how Data Engineering, Machine Learning, and AI experts can boost your business.

Talk to expert – It’s free

Data engineering for cloud-based data processing and storage.
Dominik Radwański
Service Delivery Partner
TALK TO EXPERT

From fragmented legacy systems to a cloud-native, multi cloud data platform you can scale and govern

Cloud data migration factory and automation

Cloud agnostic and multi cloud data platform design

Data Lake Migration

Cloud data migration testing and quality-by-design

Let’s talk and work together

We’ll get back to you within 4 hours on working days (Mon – Fri, 9am – 5pm CET).

Data engineering for cloud-based data processing and storage.
Dominik Radwański
Service Delivery Partner
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Cloud Migration FAQ

How do you reduce the risk of cloud data migrations for critical systems?

We start with a discovery and assessment phase, define a phased data migration to cloud strategy, and implement layered controls.

Reference architectures

Automated cloud data migration testing

Clear rollback plans

Real-time data migration reporting dashboards for your stakeholders

Can you support multi cloud and hybrid scenarios, not just a single hyperscaler?

Yes, we design cloud agnostic architectures that span on premise, private cloud and multiple public clouds.

Yes, we design cloud agnostic architectures that span on premise, private cloud and multiple public clouds, using containerization and multi cloud orchestration so workloads can run where they are most secure and cost-effective.

We already use some cloud data migration tools – do we need to replace them?

Not necessarily; we often integrate your existing data migration cloud tooling into a broader cloud data migration solution.

Fill capability gaps

Standardize patterns so teams work with a consistent playbook rather than isolated scripts

How do you handle performance and cost once we are in the cloud?

We apply FinOps and performance engineering practices from day one.

Right-sizing

Workload scheduling

Storage optimization

Continuously benchmark your big data cloud and data lake environments against agreed SLAs and budgets

Do you work only with Google Cloud data migration projects?

We have deep experience in Google Cloud but also deliver migrations on Azure and AWS.

We have deep experience in google cloud data migration, but we also deliver migrations on Azure and AWS and often run cloud to cloud data migration between providers as part of broader modernization programs.