dbt

SQL transformations with engineering quality

dbt (data build tool) is the standard tool for data transformations in the modern data stack. It enables data engineers and analysts to transform data directly in the data warehouse using SQL — following the same principles software developers use to write their code.

With dbt, transformations are versioned, tested and documented. The result is reliable, traceable and maintainable data pipelines that grow with your organisation.

dbt works with all leading cloud data warehouses — Snowflake, BigQuery, Redshift, Databricks and many more — and integrates seamlessly into existing data infrastructures.

Core features

→Modularisation — Split SQL logic into reusable models
→Automated testing — Check data quality directly in the pipeline
→Documentation — Auto-generate data lineage and descriptions
→Version control — Git-based workflow for all transformations
→Incremental models — Efficient processing of large datasets

Why we rely on dbt

Analytics engineering as a discipline
dbt bridges the worlds of data analysis and software engineering. Transformations are treated like code: versioned, peer-reviewed and automatically tested. This increases data quality and trust in reports and dashboards.
Centralised business logic
Instead of scattered SQL snippets across different BI tools, you get a single, documented source of truth. Metrics are defined once and used consistently everywhere.
Faster time-to-insight
Modular models and reusable components allow new data pipelines to be developed and deployed to production significantly faster.

Was können wir für dich tun?

Our Services dbt

Introducing dbt to your stack

We guide the introduction of dbt in your organisation: from evaluation and setup to your first production models. We take your existing infrastructure and team into account throughout.

Migrating existing transformations

Do you have SQL transformations scattered across different tools? We migrate them into a unified, testable and documented dbt codebase — structured and with minimal risk.

dbt for your team

We train your data team in dbt best practices: model structure, testing, documentation and CI/CD integration. This makes analytics engineering a lived practice in your organisation.

Dominik Imark

I'm happy to answer your question

Resources Website dbt Labs dbt Documentation

Address

Aeschengraben 13
4051 Basel, CH

Phone number

+41 (0)61 551 0012

hey@banian.ch

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Contact

dbt

SQL transformations with engineering quality

Why we rely on dbt

Our Services dbt

Dominik Imark

We look forward to hearing from you