dbt

Why choose dbt for your data stack?

dbt simplifies the daily lives of data analysts, analytics engineers and data engineers by offering them a :

• Standardized, SQL-based
• Readable, modular, automatically documented
• Secure, with built-in testing at every stage
• Automated, with model planning via orchestrators (Airflow, dbt Cloud, Azure Data Factory…)
  

This makes it possible to build a robust, industrialized and maintainable analytical foundation, where every transformation is traceable, tested, versioned and aligned with best practices.

AI and dbt: towards augmented development

dbt is a natural step in the evolution of data tools towards greater automation and intelligent assistance.

An increasing number of platforms (including dbt Cloud) now offer autocompletion, assisted documentation and automated log analysis to identify errors, slowdowns or possible optimizations.

Combined with solutions such as Snowflake + Cortex, Azure AI, or in-house plugins, dbt becomes a central building block in AI-enabled data architectures – whether to feed models, provide reliable datasets, or automate certain stages of transformation.

ActinVision can help you set up augmented data flows, where the power of dbt is put to work in concrete, industrialized AI projects.

ActinVision, your dbt transformation partner

Adopting dbt isn’t just a technological choice, it’s a cultural change in the way we conceive and maintain data.

ActinVision offers you a comprehensive approach:

• Requirements scoping and target architecture (ELT, warehouse, orchestration, etc.)
• Structuring dbt projects (repositories, models, conventions, tests)
• Integration with your CI/CD (Git, GitHub Actions, Azure DevOps…)
• Training and upskilling your teams
• Redesign or migration from traditional ETL tools
• Consulting on model industrialization and governance