Cloud Migration Consulting Services
DSC helps businesses move data infrastructure from legacy systems and on-premise environments to modern cloud data stacks. We support every stage of migration, from assessment and planning to validation, cutover, and post-migration optimization.
PARTNERS
When It's Time to Move Your Data to the Cloud
Most companies don’t wake up looking for “cloud migration services”; they’re dealing with a specific, growing problem. These are the signals that usually mean it’s time to move
- Your legacy data warehouse or on-premises infrastructure has become expensive to maintain.
- The current system doesn’t scale well as data volumes grow.
- Reporting and analytics are slow because of old infrastructure limitations.
- The business is adopting cloud SaaS tools and needs a coherent cloud data stack to support them.
- Your data team spends more time on maintenance than on analytics.
- The current architecture doesn’t support self-service BI, advanced analytics, or AI/ML.
- New data sources are difficult or slow to connect to the existing platform.
- Infrastructure costs keep growing, but the business isn’t getting more value in return.
- You’re planning modernization, expansion, M&A, or AI initiatives that legacy infrastructure can’t support.
If any of this sounds familiar, it’s a strong sign your data platform is holding your business back rather than moving it forward.
What Our Data & Cloud Migration Services Include
DSC helps growth-stage and enterprise teams move data platforms, warehouses, and pipelines to modern cloud environments without disrupting the reporting and analytics the business depends on. Our migration services cover the full lifecycle
Migration Assessment and Readiness Audit
Every migration starts with understanding what you actually have. Before moving a single table, DSC audits your current data environment to reduce risk, size up the complexity of the project, and determine which workloads should move first and which shouldn’t move yet at all.
This includes:
- An inventory of current systems and data sources
- A review of data warehouses, databases, pipelines, and reporting dependencies
- Workload and dependency mapping
- Data volume and complexity assessment
- Cloud readiness evaluation
- Data quality and migration risk assessment
- A total cost of ownership (TCO) comparison between your current infrastructure and the target cloud setup
The output is a clear migration readiness view: what can be migrated quickly, what needs modernization first, which risks are critical, and what a phased migration plan should look like.
Cloud Migration Strategy and Planning
Successful migrations are won or lost in the planning stage, not during the technical transfer of data. Once we understand your environment, DSC helps you define the strategy that will guide the entire project.
That includes:
- Target cloud platform
- Migration approach
- Phased roadmap
- Workload prioritization
- Cutover strategy
- Risk mitigation plan
- Downtime requirements
- Security and compliance considerations
- Business continuity plan
Depending on your goals and constraints, we’ll help you choose the right approach: lift-and-shift for a faster migration with minimal changes, replatforming to take advantage of cloud-native tools, or a full rebuild to modernize your data stack for long-term scalability, performance, and AI-readiness. The right choice isn’t only technical; it has to match your budget, timeline, risk tolerance, and business priorities, and that’s the lens we plan through.
Data Warehouse and Cloud Data Platform Migration
This is where legacy or on-premise data warehouses become modern, cloud-based platforms. DSC handles the migration of your core data infrastructure, including legacy databases and managed platforms, so your teams end up with a system built for where the business is headed, not just where it’s been.
This covers:
- Data warehouse migration to the cloud
- Migration from legacy databases or managed platforms
- Schema and data model migration
- Historical data transfer
- Data reconciliation between source and target systems
- Performance tuning after migration
- Integration with BI and analytics tools
We work with modern cloud data platforms such as Snowflake, and our team has hands-on experience integrating migrated environments with tools like Fivetran, dbt, and Tableau to keep reporting and analytics running smoothly on the other side.
Data Pipeline and ETL / ELT Migration
Moving your data without migrating the logic behind it is how reporting breaks. DSC migrates and modernizes the processing layer alongside the storage layer, so the pipelines feeding your dashboards and applications are just as reliable in the cloud as they were before, if not more so.
This includes:
- Migration of existing ETL / ELT workflows
- Rebuilding legacy pipelines using cloud-native tools
- Orchestration setup
- Transformation logic review
- API and SaaS integrations
- Data ingestion modernization
- Validation of transformed datasets
- Documentation and handover
We don’t just lift and drop pipeline code into a new environment. We use the migration as an opportunity to make your data workflows more reliable, more scalable, and better suited to how a cloud environment is meant to run.
Data Validation, Testing and Cutover Support
Most migration problems don’t come from the cloud platform itself; they come from data inconsistencies, broken transformations, or business logic that quietly stopped matching reality. Validation is where DSC pays the closest attention, because it’s what protects trust in your data once the migration is live.
Our validation and cutover process includes:
- Row-count checks
- Reconciliation between source and target systems
- Business logic testing
- Validation of reports and dashboards
- Performance testing
- User acceptance testing
- Rollback planning
- Parallel runs were needed
- Cutover support
Validation isn’t a final checkbox for us; it’s built into every stage of the migration, so issues get caught early instead of after go-live.
Post-Migration Optimization and Support
A migration doesn’t end at cutover. Once your platform is live in the cloud, the work shifts to making sure it runs efficiently and stays that way.
DSC supports you after go-live with:
- Performance tuning
- Query optimization
- Cost optimization
- Right-sizing of cloud resources
- Monitoring and alerting setup
- Security review
- Access control review
- Documentation
- Ongoing support during the first weeks or months after migration
If cost efficiency is a priority beyond the initial post-migration period, this is also where DSC Optimizer comes in, helping you monitor usage, catch inefficiencies, and keep cloud spend under control long after the migration itself is done.
What You Gain After a Successful Cloud Migration
Scalable Cloud Infrastructure
The data platform can scale with the business without a full rebuild.
Lower Maintenance Burden
The data team spends less time on infrastructure maintenance and more time on analytics.
Faster Reporting and Analytics
Cloud-native processing helps accelerate data workflows, dashboards, and reporting.
Cost-Controlled Environment
Cloud resources can be optimized for real workloads instead of maintaining excess on-premises capacity.
BI and AI Readiness
A modern cloud data stack creates the foundation for self-service BI, advanced analytics, and AI/ML.
Better Reliability and Security
Cloud-native backups, monitoring, access controls, and security features reduce operational risks.
Our Cloud Migration Process
Migration Assessment
Audit of current infrastructure, systems inventory, workload mapping, TCO analysis, cloud readiness evaluation, and risk assessment.
Strategy & Planning
Selection of cloud platform, migration approach, cutover strategy, phased roadmap, priorities, and risk mitigation plan.
Architecture Design
Designing target cloud architecture, storage and compute strategy, data models, pipeline design, security, and governance controls.
Migration Execution
Migrating data, pipelines, and workloads with minimal downtime. If needed — parallel runs or phased cutover.
Validation & Testing
Data reconciliation, business logic testing, performance testing, report validation, and UAT with business teams.
Optimization & Support
Performance tuning, cost optimization, monitoring setup, security review, documentation, and post-migration support.
Cloud Platforms and Technologies We Work With
Cloud data warehouses: Snowflake
Migration and integration tools: Fivetran, Airbyte
Transformation: dbt
BI and analytics tools: Tableau, Looker, Sigma Computing
Related Cloud Migration Case Studies
Related Data Services
If you’re planning a broader data transformation initiative, DSC also provides complementary consulting and implementation services that support your cloud migration strategy:
- Data Architecture Consulting
- Data Engineering Services
- Business Intelligence Consulting
- Data Governance Consulting
- Dashboard Development Services
- AI & Machine Learning Consulting
Frequently Asked Questions
What are data and cloud migration services?
Data and cloud migration services involve moving data, applications, and analytics workloads from legacy or on-premises systems to modern cloud environments. This includes planning, transferring, validating, and optimizing your data infrastructure so it performs reliably in its new environment.
What is the difference between data migration and cloud migration?
Data migration refers to moving data from one system, format, or storage location to another, which can happen entirely within on-premises environments. Cloud migration specifically means moving that data, along with associated applications and workloads, into a cloud platform such as AWS, Azure, or Google Cloud.
What is included in cloud migration consulting?
Cloud migration consulting typically includes an assessment of your current infrastructure, a migration strategy and roadmap, architecture design for the target environment, data transfer and validation, pipeline and workload migration, and post-migration support to ensure everything runs smoothly.
When should a business migrate its data infrastructure to the cloud?
Businesses often consider migration when on-premise systems become costly to maintain, when scaling becomes difficult, when performance or reliability issues arise, or when new analytics and AI initiatives require more flexible, modern infrastructure.
How long does a data warehouse migration to the cloud usually take?
Timelines vary based on data volume, system complexity, and the number of downstream integrations involved. Smaller migrations can take a few weeks, while larger, more complex environments may take several months. A proper assessment upfront helps set realistic expectations.
How do you minimize downtime during migration?
Downtime is minimized through careful planning, phased rollouts, parallel running of old and new systems where possible, and thorough testing before cutover. Coordination with downstream teams also helps prevent disruptions to daily operations.
How do you ensure data integrity and accuracy during migration?
Data integrity is maintained through validation checks at each stage of the migration, reconciliation between source and target systems, automated testing, and close monitoring to catch discrepancies before they impact business operations.
What is the difference between lift-and-shift, replatforming, and rebuilding?
Lift-and-shift moves existing systems to the cloud with minimal changes. Replatforming involves making targeted optimizations during the move, such as upgrading components without a full redesign. Rebuilding means redesigning the data infrastructure from the ground up to take full advantage of cloud-native capabilities.
Can you migrate our existing ETL or ELT pipelines?
Yes. Existing ETL or ELT pipelines can be migrated, rebuilt, or optimized as part of the migration process, depending on whether they need to be preserved as-is or modernized for better performance in the new environment.
Can you work with AWS, Azure, or Google Cloud?
Yes. Migrations can be planned and executed across major cloud providers, including AWS, Azure, and Google Cloud, depending on which platform best fits your business needs.
Can you migrate data to Snowflake, BigQuery, or Databricks?
Yes. Data can be migrated to modern cloud data platforms such as Snowflake, BigQuery, or Databricks, with the target platform selected based on your analytics, scalability, and cost requirements.
How do you handle sensitive or regulated data during migration?
Sensitive and regulated data is handled with strict access controls, encryption, and compliance considerations throughout the migration process, ensuring the new environment meets the same or stronger security and governance standards.
What happens after the migration is complete?
Once migration is complete, systems are validated against agreed benchmarks, performance is monitored, and any remaining issues are addressed. Teams are also supported as they transition to operating in the new environment.
Do you provide post-migration optimization and support?
Yes. Post-migration support includes performance tuning, cost optimization, and ongoing assistance to ensure the new infrastructure continues to run efficiently as your business scales.
Start Your Cloud Migration Journey
Whether you are migrating from a legacy on-premise warehouse, moving away from an expensive managed platform, or rebuilding your data infrastructure for analytics and AI readiness, DSC can guide you through the entire migration journey. Let’s start with a migration assessment and identify the safest path forward.
