Data Warehouse Design and Development

Centralised data platforms that make reporting accurate, analytics fast, and business intelligence accessible.

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A Single Source of Truth

We design and build data warehouses for businesses across the UK and Isle of Man. Centralised data platforms that consolidate information from across your organisation into a single, reliable source of truth - making reporting accurate, analytics fast, and business intelligence accessible to the people who need it.

The need for a data warehouse typically emerges when reporting becomes painful. When generating a weekly report requires an analyst to manually extract data from multiple systems and combine it in a spreadsheet. When the same metric shows different numbers depending on which system you query. When your operational database slows down every time someone runs a complex report. These are the symptoms of a business whose data infrastructure has not kept pace with its data needs.

Every data warehouse we design is the work of Owen Jones, OLXR's founder and lead engineer. We treat data warehousing as a serious engineering discipline - not just a place to dump data, but a carefully designed platform that serves your organisation's reporting and analytical needs reliably.

Who This Is For

Businesses whose reporting requires manual data extraction from multiple systems and spreadsheet assembly
Organisations where different teams report different numbers for the same metrics
Companies whose operational database slows down every time someone runs a complex report
Teams needing historical data analysis and trend reporting across months or years
Businesses investing in BI tools like Power BI or Tableau and needing a reliable data foundation
Organisations consolidating data from multiple source systems into a single platform

What We Deliver

Dimensional Model Design

Star and snowflake schemas optimised for reporting queries.

ETL/ELT Pipelines

Reliable data ingestion from your operational systems.

Historical Data Loading

Migration of historical data for trend analysis and long-term reporting.

Data Quality Framework

Validation, cleansing, and reconciliation rules built into every pipeline.

Reporting Layer

Views, aggregations, and calculated metrics ready for reporting tools.

BI Tool Integration

Power BI, Tableau, and other tools connected to your warehouse.

Refresh Scheduling

Automated, scheduled data updates that keep your warehouse current.

Ad-Hoc Analysis Support

Schema and access patterns designed so your analysts can run ad-hoc queries without requiring engineering help every time

Our Approach

1
Model the Business, Not the Systems

A data warehouse should reflect how your business thinks about its data - not the structures of the operational systems it draws from. We start by understanding your business domain and the questions your organisation needs to answer, then design a dimensional model that makes those questions easy to answer.

2
Prioritise Data Quality

A data warehouse that contains bad data is worse than no data warehouse at all. We build data quality validation into the ingestion pipeline - checking for referential integrity, detecting anomalies, flagging records that fail validation. Data that fails validation is not silently loaded - it is surfaced for investigation.

3
Design for Self-Service

The goal is to make reliable data accessible to non-technical users through BI tools with meaningful names, clear definitions, and pre-calculated metrics. When a warehouse is designed well, business users can answer their own questions without waiting for a developer or analyst to write a query.

Technologies We Use

SQL Server
PostgreSQL
EF Core
AWS RDS
Azure SQL
ETL/ELT
Power BI
Tableau
Python
Docker

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Frequently Asked Questions

An operational database is designed for transactional workloads - many small reads and writes, low latency, high concurrency. A data warehouse is designed for analytical workloads - large reads across historical data, complex aggregations. The structural design differs significantly.

Most businesses are well served by daily refresh. Near-real-time is possible but adds complexity. We recommend the frequency that matches your actual reporting needs rather than building unnecessary complexity.

Yes - we design the reporting layer to work with your specific BI tool, including the semantic model. We can also configure the connection and help set up initial reports and dashboards.

Ready to Build Your Data Warehouse?

Tell us about your reporting challenges. We will give you an honest view of whether a data warehouse is the right solution and what it would take to build one.

Book a Free Consultation