Data Warehouse Architecture
Your Single Source of Truth for Analytics
Design and implement modern cloud data warehouses that centralize your data, optimize query performance, and enable self-service analytics. Build a solid foundation for business intelligence and data-driven decision making.
What is Data Warehouse Architecture?
Centralized analytics infrastructure
A data warehouse is a centralized repository that stores structured data from multiple sources, optimized for analytical queries and reporting. Unlike operational databases designed for transaction processing, data warehouses are built for fast, complex queries across large datasets.
Modern cloud data warehouses like Snowflake, BigQuery, and Redshift have revolutionized data warehousing. They offer virtually unlimited scale, pay-per-query pricing, and separation of storage and compute that provides flexibility traditional warehouses cannot match.
Our data warehouse architecture services cover the complete lifecycle-from schema design and data modeling to ETL integration, query optimization, and ongoing performance tuning. We build warehouses that serve as the foundation for your entire analytics ecosystem.
Why Choose DevSimplex for Data Warehouse Architecture?
Modern warehouses built for performance and scale
Data warehouse design decisions have long-lasting impacts. A poorly designed schema leads to slow queries, complex maintenance, and frustrated analysts. We bring proven data modeling expertise to ensure your warehouse is built for success from day one.
We specialize in modern cloud data warehouses and understand the unique characteristics of each platform. Whether you need Snowflake's multi-cluster architecture, BigQuery's serverless scaling, or Redshift's performance optimization features, we design for your specific needs.
Beyond the initial build, we focus on operational excellence. This means query optimization, cost management, access controls, and documentation that enables your team to operate the warehouse confidently and cost-effectively.
Requirements & Prerequisites
Understand what you need to get started and what we can help with
Required(3)
Data Sources
Inventory of data sources to be integrated into the warehouse.
Analytics Requirements
Key business questions and reporting needs the warehouse must support.
Volume & Growth
Current data volumes and expected growth projections.
Recommended(2)
Performance SLAs
Query performance requirements for different use cases.
Access Patterns
Who needs access and what types of queries they will run.
Common Challenges & Solutions
Understand the obstacles you might face and how we address them
Slow Query Performance
Analysts waiting hours for reports, reducing productivity.
Our Solution
Optimized schema design, proper indexing, and materialized views for common queries.
Rising Costs
Cloud warehouse costs growing faster than data volumes.
Our Solution
Workload optimization, query governance, and right-sized compute resources.
Data Silos
Inconsistent metrics across departments causing confusion.
Our Solution
Unified data model with conformed dimensions and standardized business logic.
Your Dedicated Team
Meet the experts who will drive your project to success
Data Architect
Responsibility
Designs data models and warehouse architecture.
Experience
Kimball/Inmon methodologies, 10+ years
Data Engineer
Responsibility
Implements ETL processes and data integration.
Experience
5+ years data warehousing
Analytics Engineer
Responsibility
Creates data models and documentation for analysts.
Experience
dbt, SQL expert
Engagement Model
Dedicated team through implementation with knowledge transfer included.
Success Metrics
Measurable outcomes you can expect from our engagement
Query Performance
10x faster
With optimized schema
Typical Range
Cost Efficiency
40% savings
Through optimization
Typical Range
Data Freshness
Near real-time
With streaming ingestion
Typical Range
User Adoption
80%+ analysts
Self-service enabled
Typical Range
Data Warehouse ROI
Centralized analytics drives better, faster decisions.
Report Generation
90% faster
Within Post-deployment
Analyst Productivity
50% improvement
Within First quarter
Data Inconsistencies
95% reduction
Within Immediate
“These are typical results based on our engagements. Actual outcomes depend on your specific context, market conditions, and organizational readiness.”
Why Choose Us?
See how our approach compares to traditional alternatives
| Aspect | Our Approach | Traditional Approach |
|---|---|---|
| Schema Design | Optimized star/snowflake schemas Fast queries and intuitive analysis | Ad-hoc table structures |
| Scalability | Cloud-native unlimited scale Grow storage and compute independently | Fixed capacity on-premise |
| Cost Model | Pay-per-query with optimization Costs scale with actual usage | Fixed licensing costs |
Technologies We Use
Modern, battle-tested technologies for reliable and scalable solutions
Snowflake
Cloud data platform
BigQuery
Google data warehouse
Redshift
AWS data warehouse
PostgreSQL
Open source RDBMS
dbt
Data transformation
Ready to Get Started?
Let's discuss how we can help you with data engineering.