Data Warehouse
Data & TrackingAlso: DWH · Enterprise Data Warehouse · Cloud Data Warehouse
Quick definition
A centralised repository that stores large volumes of structured data from multiple sources — GA4, CRM, ad platforms, e-commerce — in a format optimised for analysis and reporting rather than real-time transactions.
How it varies across Australia
Most Australian businesses under $10M revenue don't have a formal data warehouse. The typical trigger for adoption is when marketing teams are spending more than a day per week manually combining reports from multiple platforms. At that point, the ROI of a cloud data warehouse (BigQuery or Snowflake start at low or no cost for small data volumes) is clearly positive.
Explore benchmarks →The process of extracting data from source systems (GA4, Salesforce, Shopify), transforming it into a consistent format and loading it into the data warehouse. Modern tools like Fivetran or Airbyte automate much of this process.
The structure of how data is organised in the warehouse — tables, columns, relationships and data types. A well-designed schema makes queries faster and analysis easier. A poorly designed schema creates ongoing confusion and errors.
Data warehouses are optimised for OLAP (Online Analytical Processing) — complex queries across large datasets. This differs from transactional databases (OLTP) used by your CRM or e-commerce platform, which prioritise fast individual record reads and writes.
A subset of the data warehouse focused on a specific business area — a marketing data mart might contain only campaign, website and conversion data. Useful for teams that need fast access to domain-specific data without querying the full warehouse.
Business intelligence tools that connect to the data warehouse and visualise the data for non-technical users. Looker Studio (free), Tableau and Power BI are common choices. The warehouse stores data; BI tools make it accessible.
What it actually means
A data warehouse is a centralised database purpose-built for analytical queries. Unlike the operational databases that power your CRM, e-commerce platform or ad platforms, a data warehouse is designed to hold large volumes of historical data from multiple sources and answer complex questions across them: what is our customer LTV by acquisition channel, what is our blended CPA across all paid platforms, how does retention differ by product category? The data is typically structured, cleaned and modelled before being loaded into the warehouse, making it reliable for reporting.
A data warehouse is the difference between staring at four different dashboards and actually understanding what is happening across your business.
The Australian context
BigQuery (Google) is free for the first 10GB of storage and the first 1TB of queries per month — making it accessible for Australian SMBs without upfront cost. Snowflake and Redshift (Amazon Web Services) are the other dominant options for larger organisations. Most Australian marketing agencies and data consultancies can set up a basic BigQuery + Looker Studio stack in a few days for a business with standard platform connections.
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About New Rebellion
New Rebellion is a marketing intelligence consultancy. We build tools, score Australian businesses on how their marketing actually performs, and publish Debrief every day. This dictionary is part of how we work in the open.
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