dbt

dbt helps data teams turn raw data into reliable, analytics-ready datasets in the data warehouse. It brings version control, testing, and clear documentation to streamline and scale data transformation.

Our vision on analytical data products with dbt

In the era of data-driven decision-making, dbt stands out as a transformative tool for data professionals, offering a robust framework for orchestrating data transformations and building data models. 

At Datashift, we empower organizations to build reliable, scalable, and trustworthy data transformation pipelines using dbt, turning raw data into actionable insights using engineering best practices.

Why we love to work with dbt for our clients

We focus on establishing a modern, agile, and governance-driven data transformation layer within your data warehouse using dbt. We position dbt as the central orchestrator for building business-ready data assets from your raw data.

Data Trust & Quality

Clients need to ensure their data is accurate, consistent, and reliable for decision-making.

By embedding automated testing and clear documentation in data transformations, we ensure integrity from the start, building trust in every insight.
Time-to-Insight & Agility

Clients want to get insights faster from their data and adapt quickly to changing business requirements. 

We streamline data pipeline development through modular design principles and collaborative workflows.
Technical Debt & Maintainability

Clients struggle with complex, undocumented, and difficult-to-maintain data transformation logic.

We establish a structured, version-controlled, and self-documenting transformation framework that reduces complexity, improves code readability, and ensures long-term sustainability of your data assets.

Team Empowerment & Scalability

Clients aim to enable their data teams to build and manage data products efficiently and at scale.

We transform your data professionals into empowered analytics engineers, providing them with the tools and methodologies to independently build and manage robust data products.

Join us at the dbt Global Circuit Series in Antwerp

Datashift is co-hosting alongside dbt Labs and Port of Antwerp-Bruges, We are excited to bring the community together for an evening of real stories, lessons learned, and future-proof data setups. Register to join us there.

Schedule a discovery session with our team 

Analyze your data environment and pinpoint immediate opportunities to boost your data's reliability and streamline your operations, delivering quick wins that show demonstrable ROI. We'll help you start building true internal capability and foster a data-as-a-product mindset that leads to lasting self-sufficiency.

Schedule a discovery session

The Datashift Approach

At the core of our dbt implementation approach is collaborative analytics engineering, backed by years of hands-on experience with the dbt framework. We focus not just on building, but on empowering your data teams to drive long-term value.

    FAQ on dbt

    dbt helps you transform data in your data warehouse using SQL, applying software engineering best practices like version control, testing, and documentation. You need it to build reliable, high-quality, and scalable data models, empowering your business users with trusted data.

    The choice between dbt Cloud (managed service) and dbt Core (self-managed) depends on your team's size, technical capabilities, budget, and specific infrastructure requirements. We help you evaluate these factors to make the optimal decision.

    dbt allows you to define and execute automated tests directly on your data models (e.g., uniqueness, non-null, referential integrity, etc.). This proactive testing identifies issues early in the transformation pipeline, preventing them from impacting downstream reports.

    Yes, dbt is designed to integrate seamlessly with most modern data warehouses (e.g., Snowflake, BigQuery, Redshift) and can be orchestrated with tools like Airflow. All supported data warehouse technologies can be found on this page: https://docs.getdbt.com/docs/supported-data-platforms

    Our phased approach focuses on delivering quick wins by prioritizing high-impact data models. Clients often see tangible improvements in data trust and reduced manual effort within weeks of initial implementation.

    Any more questions on dbt? Reach out!

    Contact Datashift