Data Warehousing
Data Warehousing centralises your data from multiple sources into a single, queryable repository. We build warehouses that make your data accessible, reliable, and ready for analysis.
Our process.
Data Audit & Warehouse Requirements
We audit your current data sources, volume, structure, and define warehouse requirements — schema, access patterns, query performance, and scalability.
Architecture & Schema Design
We design the data warehouse architecture, schema design (star, snowflake, or vault), ETL/ELT pipelines, and data governance framework.
Implementation & Data Migration
We build the warehouse, implement data pipelines, migrate historical data, and establish ongoing data ingestion processes.
Access Setup & Optimisation
We set up role-based access, connect BI tools, implement query optimisation, and provide documentation and training for your team.
What you get.
Questions we get asked.
Do I need a data warehouse?
If you have multiple data sources and need to run cross-source queries, generate consolidated reports, or perform advanced analytics, a data warehouse is essential. It becomes more valuable as your data grows.
What's the difference between a data warehouse and a database?
Databases are optimised for transaction processing (OLTP) — storing and retrieving individual records. Data warehouses are optimised for analytical processing (OLAP) — aggregating and querying large volumes of data across sources.
Which data warehouse should I use?
We recommend based on your needs: BigQuery for Google Cloud users, Snowflake for flexibility and performance, Redshift for AWS ecosystems, and Postgres-based solutions for smaller-scale needs.
Ready to start growing?
Free audit. No commitment. First results within 60 days or we fix it.