What is dbt?

Your business runs on data. You’ve got lots of it coming in from lots of different places. To build a competitive advantage, you’re finding ways to integrate these datasets and get a full picture of the impact of your business initiatives.

With the modern data stack, it’s easy to extract raw data from your data sources and load it into a cloud data platform. With a cloud data platform, you can ship reports and power operational use-cases with ease.

But, as your business grows, so does your data. There’s new data sets, new business logic, new use cases, and new stakeholders demanding new ways of looking at the data.

You need to standardize your data and abstract the complexity of your business logic so that everyone in the organization—whether a data engineer, BI analyst, or your executive stakeholder—can move fast with data in a scalable, cost-effective way.

This standardization needs to happen inside of the data platform—not across a bunch of BI dashboards.

That’s where dbt comes in. dbt manages this complexity—in a way that’s modular, scalable, repeatable, and governed—all directly inside of your data platform.

Data teams use dbt to transform data into cleaned, prepared, tested, ready-for-analysis datasets that can be used to power every downstream use case, whether it’s for BI reporting or to power operational use cases. With dbt, you can be confident in your data and that the decisions they inform are accurate, consistent, and shipped to downstream teams with agility.

We built dbt with two core beliefs:

1. Transformation logic should be defined in code.

2. Data teams should have the tools to be able to work like software engineers so they can treat their data assets like a product. This means that data pipelines should be: version-controlled, tested, documented, and shipped incrementally in a secure and governed way

Using dbt, data teams can ship trusted data products, faster.

Join the 100,000+ analytics engineers who are pushing the limits of data engineering to new frontiers with dbt.