What is a data warehouse and why is it so important?

A data warehouse is a central storage location where you bring together various data sources, clean them, and store them in a structured way. Think of data from your CRM system, your webshop, your marketing tools, your accounting software, and even offline systems. Unlike data that is scattered across countless Excel files, SaaS tools, and other ‘islands’, a data warehouse offers a single collection point. This is often referred to as the ‘single source of truth’.

Get in touch

Request a quote

Why is centralized data important?

One truth for the entire team – No one gets stuck in debates over whether a KPI is 1000 or 1200; everyone looks at the same numbers.
Combined insights – You can merge data from different sources. For example, link webshop data to ad spend or stock levels.
Better decision-making – With reliable, consistent data, you make faster and better decisions.
Full control and ownership – While external platforms delete data after a certain period (like GA4, Meta, and Search Console), your data warehouse stores everything for as long as you want.

In essence, a data warehouse is the ‘engine’ of your data-driven organization. Without this engine, you’ll quickly run into data source silos and inefficiencies.

Frequently Asked Questions

What is a data warehouse?

A data warehouse is a central repository where you bring together and organize data from various systems. It provides a single, reliable source of truth for your entire organization.
Want to learn more? Read the full article ‘what is a data warehouse?’ for more information.

What are the benefits of a data warehouse?

A data warehouse brings all your data together in one place, allowing you to report faster and more clearly. It gives your organization more control, deeper insights, and the freedom to store data without limitations.
Curious about all the benefits? Read the full article ‘what are the benefits of a data warehouse?’ here.

What are the trends in data warehousing?

Key trends in data warehousing include the decline of third-party data, stricter privacy regulations, and the rise of predictive analytics. Automation is also becoming more important due to a shortage of skilled personnel, and data is increasingly becoming a competitive advantage for businesses.
Want to learn more? Read the full article ‘what are the trends in data warehousing?’ here.

What are data warehouse hosting options?

The most well-known hosting options for data warehouses are Google Cloud Platform, Amazon Web Services, and Microsoft Azure — each offering strong integrations and scalable solutions. Google Cloud is especially popular due to its cost flexibility, ease of use, and strong connections with Google tools.
Want to learn more? Read the full article ‘what are data warehouse hosting options?’ here.

What are alternatives to a data warehouse?

Plug-and-play tools like Supermetrics offer a quick and easy way to collect data from marketing platforms, but they are less scalable and can become expensive as your business grows. For comprehensive and integrated data analysis, a robust data warehouse is often still the best choice.
Want to learn more? Read the full article ‘what are the alternatives to a data warehouse?’ here.

How do you set up a data warehouse?

You set up a data warehouse by first identifying your data needs and designing a data model. Next, you connect data sources, transform the data, load everything into the system, and ensure quality control and reporting.
Curious about the full approach? Check out the full article ‘how do you set up a data warehouse?’ here.

What are data warehouse use cases?

Data warehouses make it possible to gain insights into sales funnels, advertising effectiveness, inventory management, and margin optimization. They also support analyses of returns, employee performance, and customer value over time.
Want to know more? Check out the full article ‘what are data warehouse use cases?’ here.

What are the costs and ROI of a data warehouse?

The costs of a data warehouse consist of both direct and indirect components such as hosting (cloud or on-premises), development (implementation and further development), maintenance and support, tool licensing, and staff training. There are also indirect costs like change management and missed opportunities due to delays.
The ROI comes from time savings through automation, better marketing decisions thanks to integrated data, increased revenue through upsell and cross-sell opportunities, and cost savings through more efficient use of staff and inventory management.
For a full explanation, read the complete article on ‘the costs and ROI of a data warehouse’ here.

Don’t See Your Question?
Feel free to reach out.

Maximize your data impact with us

Optimal data centralization is the foundation of every data strategy. Want to take your data to the next level with our BigQuery consultants? Request a quote!

Or would you like to discuss other data challenges? We are happy to have a no-obligation conversation about how we can help.

Schedule a meeting