Solution

Cloud Migration Consulting for Legacy Data Platforms

DS Stream designs, builds and operates cloud migration programs that move analytics, AI and BI workloads from on premise to cloud-native and multi cloud data platforms. You get a discovery and assessment phase, a target architecture on Azure, AWS or GCP, phased delivery with automated testing and real-time migration reporting.

Book a 30-minute consultation

Key takeaways

Cloud migration consulting from DS Stream covers discovery and assessment, cloud migration factory, multi cloud architecture, data lake migration, migration testing and FinOps optimization.
Migrations are delivered on Azure, AWS and Google Cloud, and DS Stream also runs cloud to cloud data migration between providers as part of broader modernization programs.
The target architecture is cloud agnostic: it spans on premise, private cloud and multiple public clouds using containerization and multi cloud orchestration.
Reported outcomes include a 15-30% reduction in total cloud data platform costs within 12-18 months and a 30-50% infrastructure cost reduction over three years.
Automated cloud data migration testing, reconciliation and real-time migration reporting dashboards are used to protect reports and business users during each wave.
Existing cloud data migration tools are usually integrated rather than replaced, with capability gaps filled and patterns standardized into one playbook.

What is cloud migration consulting?

Cloud migration consulting is a packaged capability that moves analytics, AI and BI workloads from legacy on premise platforms to cloud-native and multi cloud data platforms. It combines assessment, target architecture, a phased cloud data migration strategy and automated testing, so modernization is safe, fast and measurable rather than a series of tactical fixes.

What you receive:

A discovery and assessment of your on premise warehouses, data lakes and SaaS sources
A recommended cloud agnostic architecture for your workloads
A phased cloud data migration strategy with timelines, risk assessments, cost projections and KPIs per migration wave
Automated migration testing, reconciliation and rollback plans
Real-time data migration reporting dashboards for stakeholders

Who gets the most value from cloud migration?

Data and technology leaders who have to cut legacy cost without breaking critical reporting. DS Stream works with CIOs, CTOs and Heads of IT, Chief Data Officers, CFOs and finance leadership, and with business unit leaders and product owners who depend on reliable dashboards and AI features.

CIO, CTO, Head of IT - needs a scalable cloud data strategy that reduces legacy dependence, standardizes architectures and supports AI initiatives without locking the company into a single vendor.
Chief Data Officer - needs a strategy that turns data into business outcomes, not just a platform purchase, and governance that runs rather than a policy document.
CFO and finance leadership - wants measurable ROI from data center migration to cloud, with real-time reporting that shows reduced TCO while regulatory requirements are preserved.
Business unit leaders and product owners - want faster insights, reliable dashboards and AI features that are not blocked by brittle legacy dependencies.

What changes after migration to cloud?

Legacy data centers are decommissioned and cloud compute and storage are right-sized, so infrastructure spend falls. New analytics, model and AI use cases ship 2-3x faster, incidents on reporting and data pipelines drop by 40-60%, and business units share one trusted multi cloud data platform.

Migration also shortens expansion work: rolling out cloud to cloud data migration for new regions or acquisitions takes weeks instead of months, which accelerates integration and time-to-value. Built-in quality checks, observability and clear ownership keep reports stable, and measurably higher data adoption follows once users work on a single platform instead of fragmented legacy systems.

What we deliver

Cloud migration capabilities you get

They can be used as one program or combined with your existing cloud data migration tooling.

Discovery & Assessment

Align business goals, KPIs, priority use cases and constraints with IT, operations and digital stakeholders
Map data scattered across on premise warehouses, data lakes and SaaS tools
Define a phased data migration to cloud strategy with risk assessments and cost projections

Cloud Migration Factory

Replace parallel, uncoordinated initiatives with a unified plan and governance model
Run repeatable migration waves with measurable KPIs instead of tactical fixes
Roll out cloud to cloud data migration for new regions or acquisitions in weeks instead of months

Multi Cloud Architecture

Cloud agnostic architectures spanning on premise, private cloud and multiple public clouds
Containerization and multi cloud orchestration so workloads run where they are most secure and cost-effective
Migrations delivered on Azure, AWS and Google Cloud, reducing vendor lock-in risk

Data Lake Migration

Hadoop cluster migration to a cloud data lake
Big data and BI landscape modernization
Move from legacy platforms to cloud-native AI platforms

Migration Testing

Automated cloud data migration testing that protects business users and existing reports
Clear rollback plans and reconciliation for every migration wave
Quality-by-design approach that cuts incidents on reporting and data pipelines by 40-60%
Automated dashboards and near real-time visibility into migration progress and data quality

FinOps & Optimization

FinOps and performance engineering practices applied from day one
Right-sizing, workload scheduling and storage optimization
Continuous benchmarking of big data cloud and data lake environments against agreed SLAs and budgets
70-90% forecast accuracy on cloud spend with FinOps practices

How a cloud migration engagement starts

Three steps take you from a first conversation to a phased cloud migration strategy you can fund and execute.

Discovery session
A 30-minute call where you share your current data landscape, migration goals and constraints with our cloud migration experts.
Architecture review
Our architects review your existing on premise and cloud infrastructure and recommend the optimal cloud agnostic architecture for your workloads.
Migration roadmap
You receive a phased cloud data migration strategy with timelines, risk assessments, cost projections and measurable KPIs for each migration wave.

Typical cloud migration use cases

From modernizing BI landscapes to migrating Hadoop clusters, these cloud migration solutions serve diverse operational and industry needs.

Analytics modernization - BI landscape modernization for reporting that is fragile or expensive to run on premise.
Big data migration - Hadoop migration to a cloud data lake.
Compliance migration - regulatory workload migration where requirements must be preserved end to end.
AI platform migration - graduating on premise AI platform proofs of concept to cloud-native AI platforms.
Provider migration - cloud-to-cloud migration between hyperscalers as part of a broader modernization program.
Industry solutions - industry-specific migrations shaped around sector data and operating constraints.

Typical starting points are high infrastructure costs in legacy data centers, data scattered across warehouses, lakes and SaaS tools, ETL jobs and reports that break during migration attempts, vendor lock-in risk, and uncoordinated initiatives running without a shared plan.

Business impact of migration to cloud

15-30%
Reduction in total cloud data platform costs within 12-18 months.
Source: DS Stream, Cloud Migration Consulting
30-50%
Infrastructure cost reduction over three years by decommissioning on premise data centers and right-sizing cloud compute and storage.
Source: DS Stream, Cloud Migration Consulting
25-40%
Less time spent on manual data preparation and reconciliation.
Source: DS Stream, Cloud Migration Consulting
2-3x
Faster delivery of new dashboards, models and AI use cases.
Source: DS Stream, Cloud Migration Consulting
40-60%
Fewer incidents on reporting and data pipelines after migration, thanks to built-in quality checks, observability and clear ownership.
Source: DS Stream, Cloud Migration Consulting
70-90%
Forecast accuracy on cloud spend with FinOps practices in place.
Source: DS Stream, Cloud Migration Consulting

Tactical fixes versus a structured cloud migration

How stalled modernization differs from a phased cloud data migration strategy.
Criterion	Tactical fixes on legacy platforms	Structured cloud migration with DS Stream
Ownership	Unclear ownership and parallel, uncoordinated initiatives	Unified plan, governance model and migration factory
Architecture	Vendor tools promise one-click migrations and create lock-in	Cloud agnostic architecture across on premise, private cloud and multiple public clouds
Testing	ETL jobs and reports break whenever migration starts	Automated cloud data migration testing with clear rollback plans
Progress visibility	Status and data quality known only after the fact	Near real-time migration progress and data quality dashboards
Cost control	High spend keeping legacy data centers alive	FinOps right-sizing, with 15-30% platform cost reduction in 12-18 months
Data landscape	Data scattered across warehouses, data lakes and SaaS tools	One trusted multi cloud data platform for business units

Most common questions about cloud migration

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 and 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, 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, filling capability gaps and standardizing 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, including right-sizing, workload scheduling and storage optimization. We then 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?

No. We have deep experience in Google Cloud data migration, but we also deliver migrations on Azure and AWS, and we often run cloud to cloud data migration between providers as part of broader modernization programs.

What happens in the first conversation?

A 30-minute consultation. You share where you are on your cloud data migration journey, and we walk you through concrete options to modernize your platform, reduce risk and unlock new AI and analytics value within the next 6-12 months.