During this session, we'll dive into building a production-ready flow for dbt projects on Databricks and Microsoft Fabric. We'll start with a brief introduction to what Analytics Engineering is, why the ELT approach is dominating platforms like Databricks, Snowflake, and MS Fabric right now, and how dbt helps us design the transformation layer.

After a quick demo, we’ll move on to the main part of the session, focusing on transitioning our locally running projects to production environments. We’ll discuss this topic using both Databricks and MS Fabric as examples, presenting several scenarios for tackling this challenge. We'll concentrate on key stages of the process, including:

- Automated deployment using CI/CD pipelines along with testing
- Orchestration (including ADF, Fabric Pipelines, Airflow, Workflows)
- Compute resources needed for processing (Databricks Clusters, Fabric Notebooks, Docker + ACR/ACA Jobs)
- Authentication using service principals
- Automatic generation and hosting of project documentation in Azure

Note: Besides introducing dbt, we won't go into the details of specific features during the session; our focus will be on operationalizing the processes.