Data Warehouse Design: Modern Cloud Data Platforms for Enterprise Analytics
DS Stream designs and deploys cloud-native data warehouses and lakehouses powering enterprise analytics, reporting, and AI. From dimensional modeling to data vault architectures, we deliver platforms engineered for performance, governance, and self-service.
Cloud-native data warehouse and lakehouse architectures
Modern data warehouses on Snowflake, Databricks, or BigQuery — with dimensional modeling, governance, and self-service consumption built in.
Why Legacy Data Warehouses Block Modern Analytics
Monolithic on-prem warehouses become bottlenecks — limited scale, expensive licenses, slow refresh cycles, and no support for semi-structured or streaming data. Modern enterprises need cloud-native, governed, scalable foundations.
Data Warehouse Design Capabilities
Kimball-style star schema modeling for analytics-friendly, performant query patterns.
Data Vault 2.0 modeling for agile, auditable, and scalable enterprise warehouses.
Hybrid warehouse-lake architectures combining structured analytics with flexible exploration.
Query optimization, partitioning, and clustering strategies for sub-second analytics at scale.
Semantic layer, business glossaries, and curated data products empowering analysts.
How We Build Your Data Warehouse Design Practice
Current state assessment, target architecture, modeling approach, and migration roadmap.
Deploy cloud warehouse with first data domains modeled and loaded.
Onboard additional business domains with governance and self-service patterns.
Business Impact
10x query performance through cloud-native architecture and modeling discipline.
40% lower TCO vs. legacy on-prem warehouse licenses and infrastructure.
Self-service analytics unblocking business teams from engineering bottlenecks.
Who This Is For
Use Cases for Data Warehouse Design
We deliver Data Warehouse Design engagements across industries with deep vertical expertise.
Most Common Questions
Each excels in different scenarios — we recommend based on your existing cloud, analytics patterns, and team skills.
Kimball for analytics-friendly, Data Vault for highly regulated/auditable scenarios. Often hybrid approaches work best.
First domain live in 10 weeks. Full enterprise migration typically 12–18 months in priority waves.
Yes — dbt is our standard for transformation logic with version control, testing, and documentation built in.
Ready to Modernize Your Data Warehouse Design Practice?
Book a free 30-minute review. We will assess current state, identify wins, and outline a path to production-grade delivery.
Architecture Workshop
3-day workshop to align warehouse strategy with business analytics needs.
Foundation Build
Deploy cloud warehouse foundation with first domain modeled in 10 weeks.
Domain Expansion
Onboard additional domains in waves with self-service consumption patterns.