Managed cloud data services
DS Stream designs and operates managed cloud services that unify your data across clouds, protect sensitive assets, and modernize analytics without disrupting the business. You get a resilient cloud data platform that lowers total cost of ownership, cuts manual data preparation, and accelerates time to insight for analytics and AI teams.
Key takeaways
- DS Stream designs, builds and operates managed cloud data platforms that unify fragmented data, embed data protection, and modernize analytics without disrupting the business.
- The platform spans Azure, AWS, Google Cloud and SaaS sources such as Salesforce, SAP and Snowflake, so governance stays consistent without vendor lock-in.
- Reported outcomes include a 15-30% reduction in total cloud data platform costs within 12-18 months and 25-40% less time spent on manual data preparation.
- Standardized cloud data integration and reusable data products support 2-3x faster delivery of new dashboards, models and AI use cases.
- Data migration is planned in phases with automated testing and rollback options, so you avoid long freezes and paying twice for parallel stacks.
What are managed cloud data services?
Managed cloud data services mean DS Stream designs, builds and operates your cloud data platform end to end. We connect fragmented sources into one governed foundation, embed data protection and compliance in every layer, and run the environment across Azure, AWS and Google Cloud with cost optimization built in from day one.
The scope covers four areas named on this page:
- Cloud data platform - a governed, business-ready foundation instead of scattered systems.
- Data protection - access, encryption and monitoring controls that hold across regions and providers.
- Data integration - standardized connections between ERP, CRM, web analytics and custom applications.
- Multi-cloud governance - consistent policies and visibility across providers and SaaS platforms.
Who gets the most value from a modern cloud data platform?
Leaders who depend on trusted, shared data: CIOs and CTOs standardizing architectures, CISOs who need verifiable data security in cloud, analytics and AI leaders fighting quality and lineage issues, marketing and sales leaders measuring ROI, and COOs who need predictable visibility into operational KPIs.
Roles and what they need
- CIO / CTO / Head of IT - a scalable cloud data strategy that reduces legacy dependence, standardizes architectures and supports AI without single-vendor lock-in.
- CISO / Head of Security & Risk - consistent controls for access, encryption and monitoring across regions and providers.
- Chief Digital Officer / Head of Analytics & AI - reliable, high-quality data for analytics, experimentation and machine learning, without constant firefighting around quality and lineage.
- CMO / VP Marketing and sales leaders - integrated marketing and sales data to personalize campaigns, align with sales and measure ROI across touchpoints.
- COO / Head of Operations - clear visibility into KPIs across plants, warehouses and service delivery.
What changes for the business once we modernize cloud data?
You move from reactive reporting to proactive, real-time decision-making across departments, with self-service access to trusted data. That shortens planning cycles, reduces manual work, and unlocks revenue and efficiency opportunities that legacy data stacks cannot support. Analytics and AI teams stop reconciling numbers and start shipping use cases.
Before modernization, reporting, finance and marketing teams lose days reconciling spreadsheets because data sits across on-prem, SaaS and multiple clouds with no unified cloud data management platform. Afterwards, the same numbers come from one governed source, and security and risk leaders can see who accesses what across the multi-cloud estate.
Transform your data infrastructure
Each one is delivered and then operated, not handed over as documentation.
Unified data foundation
- Connect fragmented data sources into one governed platform
- Eliminate silos between marketing, sales, finance and operations
- Replace manual reconciliation with a single trusted source for reporting
Security-first architecture
- Embed data protection and compliance into every layer
- Reduce breach risk and simplify regulatory audits
- Apply consistent access, encryption and monitoring controls across regions and providers
Accelerated time to insight
- Ship dashboards, models and AI use cases 2-3x faster
- Reusable data products eliminate repetitive work
- Solve ingestion, quality and lineage first so AI use cases hit fewer production incidents
Cost-optimized operations
- Reduce infrastructure and license costs by 15-30%
- FinOps practices align cloud spend with business value
- Optimize storage tiers, query patterns and managed services consumption
Multi-cloud freedom
- Work seamlessly across Azure, AWS and Google Cloud
- Consistent governance without vendor lock-in
- Extend the same governance to SaaS platforms such as Salesforce, SAP and Snowflake
How we engage on a cloud data platform
Four stages, from the first call to continuous optimization of the running platform.
Discovery consultation
A 30-minute call to discuss your cloud data challenges, goals and current infrastructure. We map out initial recommendations and next steps.
Architecture assessment
Our team reviews your current data architecture, identifies quick wins and proposes a phased roadmap for migration and modernization.
Implementation and governance
We design, build and operate your cloud data platform with security, governance and cost optimization built in from day one.
Ongoing optimization
We continuously monitor, tune and evolve your cloud data environment so it keeps delivering business value over time.
Where cloud data changes the way you operate
Cloud data management changes operations across industries by enabling real-time insights, automation and data-driven decision-making. The use cases we see most often:
- Retail and e-commerce - unification of POS, web and loyalty data.
- Financial services - governance and MLOps for models in production.
- Manufacturing and logistics - predictive maintenance and supply-chain visibility.
- Healthcare and life sciences - governed data for regulated analytics.
- Subscription and SaaS businesses - retention, upsell and customer health scoring.
If your priority is moving workloads first, start with cloud migration; if it is the pipelines that feed the platform, start with data ingestion.
Business impact of a managed cloud data solution
15-30%
Reduction in total cloud data platform costs within 12-18 months by optimizing storage tiers, query patterns and managed cloud services consumption, based on recent FinOps KPI benchmarks.
Source: DS Stream, Managed cloud data services
25-40%
Less time spent on manual data preparation and reconciliation for analytics teams after centralizing data in a governed cloud data management platform.
Source: DS Stream, Managed cloud data services
2-3x
Faster delivery of new dashboards, models and AI use cases thanks to standardized cloud data integration services and reusable data products.
Source: DS Stream, Managed cloud data services
70-90%
Forecast accuracy on cloud spend when multi-cloud data management is combined with FinOps KPIs such as forecast accuracy, waste reduction and unit cost per workload.
Source: DS Stream, Managed cloud data services
20-40%
Improvement in marketing ROI when integrated marketing and sales data clouds drive better segmentation, personalization and attribution.
Source: DS Stream, Managed cloud data services
Fragmented data estate vs. managed cloud data platform
| Criterion | Fragmented data estate | Managed cloud data platform |
|---|---|---|
| Access to numbers | Data scattered across on-prem, SaaS and multiple clouds | One governed platform with self-service access to trusted data |
| Reporting effort | Reporting, finance and marketing teams lose days reconciling spreadsheets | 25-40% less time spent on manual data preparation |
| Data protection | Protection and regulatory controls are unclear, exposing the business to audits and fines | Protection and compliance embedded in every layer, audits simplified |
| Integration | Slow, brittle, manual links between ERP, CRM, web analytics and custom applications | Standardized integration services and reusable data products |
| Cost | Paying twice for infrastructure and licenses during migration, with no plan to retire legacy | 15-30% lower platform costs within 12-18 months, FinOps-aligned spend |
| Multi-cloud control | No visibility into who accesses what across providers | Consistent governance across Azure, AWS and Google Cloud without lock-in |
| Delivery speed | Analytics and AI initiatives stall on integration and governance issues | 2-3x faster delivery of dashboards, models and AI use cases |
What makes DS Stream the right partner for your cloud data journey?
How do you reduce the risk and cost of data migration to Azure cloud or other platforms?
We plan data migration to Azure cloud and other environments in phases, starting with high-impact domains, automated testing and rollback options, so you avoid long freezes and parallel stacks. After migration we optimize storage tiers, compute and licensing to lower the run-rate cost of the platform.
Can you work across multiple clouds and existing tools?
Yes. We design architectures and governance that span Azure, AWS, Google Cloud and SaaS platforms such as Salesforce, SAP and Snowflake. The aim is a coherent multi-cloud data management strategy rather than forcing all workloads into a single provider, so governance stays consistent without vendor lock-in.
How does this support AI and advanced analytics?
A well-designed cloud data platform with high-quality, governed data is the foundation for reliable machine learning and GenAI initiatives. By solving ingestion, quality and lineage first, your teams ship AI use cases faster and with far fewer production incidents.
What changes for the business once we modernize cloud data?
You move from reactive reporting to proactive, real-time decision-making across departments, with self-service access to trusted data. This shortens planning cycles, reduces manual work and unlocks revenue and efficiency opportunities that legacy data stacks cannot support.
Which teams and industries use this most?
CIOs, CISOs, analytics and AI leaders, marketing and sales leaders, and operations leaders all draw on the same platform. Typical use cases include POS, web and loyalty data unification in retail and e-commerce, governance and MLOps in financial services, predictive maintenance and supply-chain visibility in manufacturing and logistics, healthcare and life sciences data, and customer health scoring in subscription businesses.
What is the first step to get started?
Book a 30-minute consultation about your cloud data platform. We discuss your challenges, goals and current infrastructure, then map initial recommendations and next steps. The following stage is an architecture assessment that identifies quick wins and proposes a phased roadmap for migration and modernization.
Related solutions and services
- Cloud MigrationThe phased migration path into the cloud data platform, including retirement of legacy systems.
- Cloud SolutionsThe wider cloud capability set across Azure, AWS and Google Cloud that this platform runs on.
- Data GovernanceThe policies, access controls and lineage that make multi-cloud governance enforceable.
- Data IntegrationConnecting ERP, CRM, web analytics and custom applications into the governed foundation.
- Data Engineering servicesThe engineering work behind pipelines, warehouses and data quality on the platform.
Book a 30-minute consultation about your cloud data platform
If you are planning a cloud data strategy, modernizing warehouses, or consolidating data across clouds, DS Stream can help you design, build and run the right solution. Our experts combine architecture, engineering and governance so your managed cloud services deliver tangible business value, not just new infrastructure.
Book a 30-minute consultation