Warehouse Architecture and Design
We design the right warehouse for your scale, cost and use cases.
Data Warehouse Services
Data Warehouse Services
Trusted across 20+ countries by Fortune 500 companies and growth-stage brands
We design and build cloud data warehouses that give your organisation one trusted, scalable source of truth, so every team reports from the same numbers. Over a decade of experience, 250+ digital solutions delivered.
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What is a data warehouse?
A data warehouse is a central store that brings together data from across your systems, structured and modelled for fast, consistent analytics and reporting. Unlike scattered databases and spreadsheets, it gives one governed version of the truth. Noseberry builds cloud data warehouses on platforms like Snowflake, BigQuery and Redshift, modelled for performance and designed to feed both BI and AI.
Key takeaways
- A data warehouse is the central, modelled source of truth for analytics.
- Cloud warehouses like Snowflake and BigQuery scale compute and storage independently.
- Good dimensional modelling is what makes queries fast and metrics consistent.
- The warehouse feeds both BI dashboards and AI models.
2M+Lives touched
15+Fortune 500 clients
20+Countries served
250+Digital solutions delivered
What we do
Our data warehouse services
Cloud Warehouse Build
We build on Snowflake, BigQuery, Redshift or Azure Synapse.
Dimensional Modelling
Star and snowflake schemas that make analytics fast and consistent.
Warehouse Migration
We move you off legacy or on-premise warehouses to the cloud.
Performance and Cost Optimisation
We tune queries, storage and compute to control spend.
Integration with BI and AI
We connect the warehouse to reporting and machine learning.
Where it delivers value
Where a data warehouse delivers value
One source of truth across departments
Fast, consistent executive and operational reporting
A governed foundation for AI and machine learning
Lower cost than scaling fragile databases
Historical analysis and trend tracking at scale
How we work
Our five-phase process
We model a priority data domain first, prove the value, then expand the warehouse across the business.
1
Discovery and Audit
We map your sources, metrics and reporting needs.
2
Strategy and Roadmap
We prioritise a data domain and design the model.
3
Rapid Proof of Concept
We model a priority domain first and prove the value.
4
Build and Integrate
We build the warehouse and connect BI and AI.
5
Deploy and Optimize
We tune performance and cost, then expand across the business.
Technology we use
Warehouses
- Snowflake
- BigQuery
- Redshift
- Azure Synapse
Modelling & transformation
- dbt
- SQL
Integration
- Airflow
- Kafka
- CDC tooling
Cloud
- AWS
- Azure
- Google Cloud
Security and compliance
Governed, from row to report
Warehouses are built with encryption, role-based and row-level access, and audit trails. We build to GDPR, HIPAA and SOC 2, deployed on AWS, Google Cloud and Azure.
GDPRHIPAASOC 2
Real success storiesFinTech · Digital Insurer PropTech · Real-estate marketplace E-Commerce · Retail leader
Outcomes we have driven
Challenge
Fragmented reporting meant every team quoted different numbers.
Solution
A governed cloud warehouse with disciplined dimensional modelling.
Impact
One source of truth, and a foundation that caught 93% of fraud pre-payout.
Challenge
Slow, inconsistent reporting across markets.
Solution
A Snowflake warehouse modelled for consistent, fast analytics.
Impact
40% faster reporting and valuations.
Challenge
No trusted base for personalization and analytics.
Solution
A warehouse feeding both BI and the recommendation engine.
Impact
+28% lift in conversion rate.
Sector-anonymised outcomes shown until named clients are approved.
Why Noseberry
Why choose Noseberry for data warehousing
Specialist
AI, Cloud and Data is our core, no generalist dilution.
Modelled for trust
Consistent metrics through disciplined modelling.
Cost-aware
We tune for performance and spend from the start.
Proven at scale
250+ solutions delivered across 20+ countries.
Data warehousing, answered.
A database runs applications and transactions. A data warehouse is built for analytics, consolidating and modelling data from many systems for fast reporting.
It depends on your stack and needs. Snowflake, BigQuery and Redshift each have strengths, and we recommend the right fit rather than a default.
A warehouse is optimised for structured, modelled analytics. A lakehouse unifies structured and unstructured data for both analytics and AI. We build both and advise on the right choice.
Yes. We migrate legacy and on-premise warehouses to the cloud in phases, with validation at each step.
Through query tuning, storage design and compute management, so you scale value without runaway spend.
Need one source of truth?
Book your free 30-minute strategy session and we will design your data warehouse.
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