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dbt – Efficiently operationalize transformations in the Modern Data Stack

Discover how to automate your data transformations directly in your target system using dbt (data build tool). Scalable, version-controlled and seamlessly integrated into the Modern Data Stack — from dbt Core to dbt Cloud.

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What makes dbt special?

Modern data landscapes consist of many moving parts, from ETL pipelines to cloud warehouses to governance systems. dbt simplifies this complexity by operationalizing data transformations directly in the target system. The result is an approach that is efficient, transparent and built for teamwork.

dbt (data build tool) is a powerful open-source framework that brings ELT transformations directly into modern cloud data platforms. It enables data teams to develop SQL models as repeatable, version-controlled and testable pipelines that integrate seamlessly into the Modern Data Stack.

Since 2024, dbt has introduced major enhancements across dbt Core and dbt Cloud, raising automation, governance and AI-assisted development to a new level. This makes dbt a central tool for data-driven organizations aiming for transparency, scalability and efficiency in their data engineering processes.

How we support you with dbt

As a certified dbt partner, we guide you in building a future-ready data stack, from technical implementation to governance. We ensure that your data processes run cleanly, scalably and fully automated.

Modeling and Transformation

We design modular, reusable SQL models that run directly in your target system.

Quality and Transparency with dbt and Documentation

Out-of-the-box tests and schema contracts, plus auto-generated project documentation with lineage, give you high transparency and quality.

Orchestration and Operations

Job setup, scheduling, logging, CI workflows, artifacts and alerts — all automated and reliable.

Governance and Lineage

Interactive DAGs and column-level lineage that make data flows and the impact of changes visible.

Semantic Layer and Metrics

Unified KPI definitions and dynamic SQL generation across platforms.

Developer Experience and AI Assistance

Using the Studio IDE and dbt Copilot to code, test and document your work — faster and smarter.

Modeling and Transformation

We design modular, reusable SQL models that run directly in your target system.

Quality and Transparency with dbt and Documentation

Out-of-the-box tests and schema contracts, plus auto-generated project documentation with lineage, give you high transparency and quality.

Orchestration and Operations

Job setup, scheduling, logging, CI workflows, artifacts and alerts — all automated and reliable.

Governance and Lineage

Interactive DAGs and column-level lineage that make data flows and the impact of changes visible.

Semantic Layer and Metrics

Unified KPI definitions and dynamic SQL generation across platforms.

Developer Experience and AI Assistance

Using the Studio IDE and dbt Copilot to code, test and document your work — faster and smarter.

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Free dbt Check

Together, we assess how well your data stack is positioned for dbt — from architecture and governance to automation. Within just a few days, you will receive a clear evaluation and actionable recommendations for your transformation.

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dbt as a central standard in the Modern Data Stack

As a tool-agnostic partner, we see dbt (data build tool) as the standard for modern, SQL-based transformations in the Modern Data Stack. dbt operationalizes data models directly in the target system, delivering transparency, version control and full automation.

With its API-first approach, dbt integrates seamlessly into existing cloud architectures and unifies data integration, transformation and governance into an end-to-end pipeline — whether organizations work with Snowflake, Databricks, BigQuery or Redshift.

Compared to traditional ETL or script-based solutions, dbt offers clear advantages:

  • Transformation in the target system instead of on separate servers
  • Versioned and testable pipelines through Git integration and automated validations
  • Documentation and lineage for full transparency
  • Scalability and governance by design through reproducible models

dbt also stands out through deep integration with other Modern Data Stack components:

  • Orchstration: Airflow, Prefect, Dagster, Cloud Scheduler
  • Data ingestion: Fivetran, Airbyte, Matillion, Qlik Talend Cloud
  • Visualization and BI: Power BI, Looker, Tableau (via the dbt Semantic Layer)
  • DataOps: GitHub Actions, GitLab CI, Azeure DevOps
  • Clouds: AWS, Azure, GCP with open interfaces
  • Governance: lineage, model contracts and automated tests

In real-world projects, the impact is clear. Teams become productive faster, especially when modernizing data warehouses, building lakehouses or introducing self-service analytics. dbt connects tools, clouds and teams into a consistent data transformation landscape that gives organizations transparency, speed and control over their data.

Get expert guidance today

Ready to take the next step?

Mitarbeiterfoto Kevin Nguyen

Kevin Nguyen
Head of Sales

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FAQs

No. dbt Core provides all essential functionality for free. dbt Cloud becomes valuable when you need scheduling, a user interface, API access or advanced governance features.

Yes. dbt is primarily SQL-based. Python models are optional and extend the flexibility of dbt, for example for complex transformations or ML preprocessing.

dbt can be integrated into common orchestration tools such as Airflow, Prefect and Dagster, as well as SaaS-based integration platforms, using its APIs and CLI. This allows it to become a seamless part of your existing ELT and automation workflows.