DBT for ETL - What's The Fuss About?

Your dashboards and AI initiatives are only as credible as the transformation layer underneath them. Many organizations still rely on “hero SQL,” fragile stored procedures, or opaque ETL jobs; making change slow, quality inconsistent, and ownership unclear. 

In this session, we demystify dbt (data build tool) and why it’s become the go-to approach for modernizing transformations: dbt focuses on the “T” in ELT by building modular SQL models inside your warehouse/lakehouse, with version control, automated testing, documentation, and lineage baked into the workflow.

This is a decision-maker–friendly webinar: we’ll translate dbt’s technical concepts into business outcomes:

• Ship changes faster with less risk by treating transformations like software (reviewable, testable, repeatable).
• Increase trust in KPIs by standardizing definitions and moving toward governed, reusable metrics (reducing “whose number is right?” debates).
• Fit into your Microsoft ecosystem: we’ll show how dbt can be operationalized with Microsoft Fabric (including dbt Jobs in Fabric and Databricks experiences) for teams standardizing on the Microsoft platform.

We’ll close with a pragmatic roadmap: when dbt is a fit, what prerequisites matter (team skills, modeling approach, CI/CD), and where targeted consulting accelerates results—like setting up a “transformation factory,” establishing testing standards, KPI governance, and enablement so your team becomes self-sufficient.

After this session you'll...

• Understand how dbt makes your transformation layer faster, more reliable, and business-ready by treating data work like software.
• See how to increase trust in KPIs and align teams with standardized, governed, reusable metrics.
• Know when and how to implement dbt in a Microsoft ecosystem, with a clear, pragmatic roadmap to get value quickly.