A data warehouse is a key component of most scalable reporting solutions. Every Kaivo plan includes a fully managed BigQuery data warehouse, at no extra cost. It works as a centralized storage for all your data and gives a boost to the performance of your Business Intelligence and AI analysis. And it does this without requiring you to hire a data engineer or manage any infrastructure yourself.

Benefits of a data warehouse

Centralized location for all analytical data

A data warehouse provides a single, unified location for storing data from various sources, reducing silos and making it easier to manage and analyze data. By centralizing your data, you streamline access and ensure consistency across your organization.

Data available in all your tools

With your data stored in a centralized warehouse, it becomes accessible to all your preferred business intelligence (BI), AI, and analytics tools. This allows you to create seamless reports, dashboards, and analyses using tools like Power BI, Tableau, Data Studio (formerly Looker Studio), Metabase, Excel, or Claude, without needing multiple data connections.

Historical data is always preserved

Many source systems only give you access to a limited window of data, such as recent months or just the current state, through their apps or APIs. A data warehouse captures and retains this data over time, so you keep historical records for trend analysis and long-term comparisons, even after that window closes in the original source. With Kaivo, this history is kept for 36 months by default, with deeper historical tracking available as an add-on.

Combine data from multiple sources

By bringing data from different sources into a single warehouse, you can easily combine datasets to get a complete view of your business. This allows for deeper insights and better correlations across different areas like marketing, sales, and customer behavior.

Avoid duplicate work

Clean, process, and combine data in your warehouse. The end result is available in all your data tools, so you don't have to do the same work in multiple places. This both saves time and ensures better data accuracy. It also means that if a source app changes its API or renames a field, that's handled centrally in your warehouse, instead of breaking every downstream report.

Higher quality, more consistent data

By consolidating and standardizing data from multiple sources, a data warehouse helps improve data quality. For example, it's easy to keep dates, currencies, and naming conventions consistent between different data sources, instead of reconciling them separately in every report.

Freedom to choose, and change, your tools

Because your data lives in a central warehouse rather than inside a specific BI tool, you're not locked into one dashboard or analytics product. You can switch to a different reporting or AI tool later, or use several side by side, without rebuilding your data pipelines each time.

A managed warehouse, without the overhead

With Kaivo, the warehouse itself runs on Kaivo's own Google Cloud infrastructure. That means there's no separate Google Cloud account to set up, no infrastructure billing to manage, and no need for in-house BigQuery expertise. As long as your subscription is active, your data stays available to the BI and AI tools you've connected.

A foundation for AI-powered analytics

Asking questions about your business in plain language, through tools like Claude, depends on your data being structured and centralized in one place. A data warehouse is the infrastructure that makes this kind of AI-assisted analysis possible, not just today's dashboards but tomorrow's AI workflows too.

How Kaivo fits in

Kaivo connects to 500+ data sources in a no-code environment and automatically sets up a fully managed BigQuery data warehouse for you, with no separate infrastructure to configure or maintain. The warehouse itself is included in the Kaivo Platform subscription, along with a monthly allowance of BigQuery usage; each data source you connect is billed separately depending on the connector. This means you get all the benefits above without needing in-house data engineering expertise.