Cloud Data Platform
Architecture
Design and implementation of scalable, cost-optimized data architectures on Azure, AWS, and GCP.
Cloud Data Practice
Cloud Data Engineering With Depth
The Challenges We Solve
Cloud data modernization involves more than moving workloads to a cloud platform. Organizations need to determine which data services fit their architecture, workloads, security requirements, governance model, performance needs, and cost objectives. The challenge becomes even greater when data spans legacy systems, cloud platforms, SaaS applications, and hybrid or multi-cloud environments.
Successful cloud data platforms require architecture that balances scalability and performance with security, governance, operational resilience, and cost.
Our Approach
At InfoPeople, we work across the full range of cloud data services from managed databases, data warehousing, streaming infrastructure, ML platforms, to the security and governance layers that regulated organizations require. Rather than recommending a platform and building around it, we evaluate your requirements and recommend the platform or multi-platform approach that actually fits.
Our cloud data practitioners have operated within FedRAMP, HIPAA, CJIS, GDPR, and CCPA constraints and delivered production data workloads across Azure, AWS, and GCP, with the hands-on depth that comes from operating in each environment at scale.
Our Cloud Data Practice Capabilities
Cloud Data Platform
Managed Database
Services
Selection, deployment, and optimization of Azure SQL, AWS RDS, Cloud SQL, and other managed databases, including migration.
Data Warehousing
Implementation of Azure Synapse, AWS Redshift, and BigQuery, including schema design, ELT, and cost management.
Streaming and
Real-Time Data
Infrastructure
Event-driven architecture using Event Hubs, Kinesis, and Pub/Sub for real-time analytics and operational systems.
Cloud-Native ML
Platform Deployment
Setup and optimization of Azure ML, SageMaker, and Vertex AI, including deployment, retraining, and governance.
Our Compliance Frameworks
Insights and Resources
Exotic insurance platform transforms underwriting with AI-native valuation and risk intelligence
A unified AI-native valuation infrastructure enabled an exotic insurance provider to reduce underwriting latency, improve pricing precision, and strengthen capital resilience across exotic risk categories.
Global digital publisher strengthens revenue predictability with AI-powered RFP and forecasting engine
A unified AI-backed revenue intelligence platform helped a global publisher reduce forecast variance, improve RFP win rates, and align inventory allocation with probabilistic demand modeling.
FAQs
The right platform depends on your existing infrastructure, compliance requirements, and team expertise. Our practitioners work across Azure, AWS, and GCP directly, which allows us to recommend based on your environment rather than steering every client toward a single platform.
Yes. Our practice has operated within FedRAMP, HIPAA, CJIS, GDPR, and CCPA constraints, with particular depth in Azure-based government and public sector data environments.
Yes. Several of our data and AI platform engagements have been deployed across AWS and GCP in parallel for clients operating multi-cloud environments, and our team is not built around a single-platform worldview.
Get Cloud Data Engineering Depth
Work with expert practitioners who operate production data workloads across Azure, AWS, and
GCP, including in regulated environments.