Services
Cloud-Native Data Lakes & Warehouses

Cloud-Native Data Lakes & Warehouses in the US

Stralya designs and delivers robust, cloud-native data lakes and warehouses that give your organization a single, reliable source of truth. From architecture to implementation and optimization, we take full ownership of your data platform so your teams can trust every dashboard, model and decision.

Service Scope

What Our Data Lakes & Warehouses Service Includes

From first whiteboard sketch to a fully operational, documented and monitored platform, Stralya covers the full lifecycle of your data lake or warehouse initiative. Our focus is always the same: a trustworthy, scalable foundation for analytics, AI and digital products.

Core Deliverables

Current-state audit of data sources, existing pipelines, reports and governance.

Target cloud-native architecture for data lake, data warehouse or lakehouse, aligned with your cloud strategy.

Implementation of secure data ingestion from CRMs, ERPs, web applications, SaaS tools and third-party APIs.

Design and build of curated data models optimized for BI, reporting and advanced analytics.

Orchestration, monitoring and alerting for all data pipelines, with clear SLAs.

Documentation, runbooks and knowledge transfer sessions for your internal teams.

Optional Add-ons

Project rescue and stabilization of existing data platforms and pipelines.

Self-service analytics enablement, including semantic layers and governed data access.

Integration with AI/ML workflows, feature stores and model monitoring.

Long-term managed services and SLAs for monitoring, optimization and evolution.

Support for regulatory reporting, audit trails and compliance documentation in the US and internationally.

Every engagement is tailored to your organization’s maturity, industry and internal capabilities. We can either design and deliver the full platform for you or work alongside your existing data team as a senior extension to accelerate delivery and raise quality standards.

Designed for the Most Demanding US Organizations

Enterprises and Public Sector

We help large organizations consolidate complex, siloed data landscapes into a single, governed platform that powers executive reporting, compliance and digital services for citizens or customers.

Startups and Scale-Ups

For fast-growing companies, we create lean but scalable architectures that support rapid experimentation, product analytics and investor-grade reporting without locking you into fragile quick fixes.

SMBs in Digital Transformation

We work with SMBs modernizing from spreadsheets and legacy systems, giving them a modern data backbone that supports better decisions, automation and future digital initiatives.

Delivery Approach

How We Deliver Data Lakes & Warehouses That You Can Trust

Our approach is simple but rigorous: clarify the business questions first, then design the minimum robust architecture that will answer them reliably at scale. We avoid over-engineering, favor proven cloud-native patterns, and document everything so your internal teams can operate and evolve the platform with confidence.

We start with workshops involving your technical and business stakeholders (CTO, CIO, Head of Data, Finance, Operations). We map your data sources, reporting pain points, existing pipelines and constraints (compliance, residency, SLAs). The outcome is a clear picture of where you are and what must change.

Based on your objectives—self-service BI, executive dashboards, AI/ML readiness, real-time analytics—we design a cloud-native architecture on AWS, Azure or GCP. We define ingestion patterns, storage layers, modeling approach, security and governance. You receive a detailed scope, timeline and fixed-price proposal with explicit success criteria.

We build the core building blocks: connectors to your systems, data lake or raw zone, curated warehouse models, orchestration and monitoring. We implement best practices for partitioning, indexing, cost control and performance. Every component is versioned, tested and documented.

We validate data quality and performance with real workloads and representative dashboards. We fine-tune queries, storage classes and scheduling to meet SLAs. Finally, we train your teams, hand over documentation and, if needed, set up a long-term support and evolution plan.

Find Commonly Asked Questions

Not always. In some cases, a well-designed cloud data warehouse is enough. In others—especially when you work with semi-structured data, data science use cases or large historical datasets—a data lake combined with a warehouse is more appropriate. During discovery, we analyze your use cases, volumes and team skills to recommend the simplest architecture that will scale with you.

We design and implement architectures on all major cloud providers used by US companies: AWS, Microsoft Azure and Google Cloud Platform. We select the right services—such as Redshift, BigQuery, Snowflake, Azure Synapse, Databricks or native lakehouse solutions—based on your existing ecosystem, budget and long-term strategy.

Yes. Many of our B2B engagements start as project rescues. We audit your current pipelines, storage, models and dashboards, identify root causes for instability or poor performance, and propose a phased remediation plan. Our fixed-price model ensures you know exactly what we will stabilize and by when.

Security and governance are core to our architectures. We design with least-privilege access, encryption at rest and in transit, role-based access control, detailed logging and monitoring. We also take into account US regulations and industry standards, as well as any internal policies you have around data residency and auditability.

Timelines depend on complexity and number of data sources, but many clients see a first production-ready version within 8 to 12 weeks. We prioritize high-value use cases first—such as executive dashboards or core revenue reporting—so you get tangible business value early while we continue to expand coverage.

Case Studies