dbt Global Circuit Series: Belgium dbt Meetup #11 (in-person)

The 11th edition of the Belgium dbt Meetup will take place in Antwerp on June 24th.

dbt Meetups are networking events open to all folks working with data! Talks predominantly focus on community members' experience with dbt, however, you'll catch presentations on broader topics such as analytics engineering, data stacks, data ops, modeling, testing, and team structures.

🏠Venue Host & Catering Provider: Port of Antwerp-Bruges, Zaha Hadidplein 1, 2030 Antwerp
🤝Organizers: Sam Debruyn & Cedric Raeymaeckers
🚆 Getting there: Parking is available under the building (private parking), with the entrance located on Mexicostraat. When entering the parking, you can indicate that you are attending the dbt meetup, and you will be granted access.

To attend, please read the Health and Safety Policy and Terms of Participation: https://www.getdbt.com/legal/health-and-safety-policy

Our venue has capacity limits, so please only RSVP if you intend to come. Reach out - send a message in #local-belgium on Slack - if you need to cancel last minute or change your RSVP status on the Meetup to "Not Going."

📝Agenda:

• 18h00: welcome with food & drinks
• 18h45: start presentations
• 20h30: networking & drinks

🗣️Presentations:

One dbt repo, two targets: parallel dbt deployments on Azure SQL & Databricks
We’ll start with a walkthrough of the technical setup of dbt at the Port of Antwerp-Bruges, in the context of a migration to Databricks. Then we'll dive into how we handle deploying dbt to multiple targets for the duration of the migration. Finally we'll compare both environments with insights from an analytics engineering perspective.
by Emiel Ackermann, Technical Lead at Port of Antwerp-Bruges & Nicolas Jonckheere, Lead Analytics Engineer at Datashift

A strategic approach to testing with Data Products in dbt
With data teams' growing ambition to build business automation, AI systems, or customer-facing products, we must shift our mindset about data quality. Mechanically applied testing will not be enough; we need a more robust strategy similar to software engineering. In this talk, I outline a new approach to data testing and observability anchored in the ‘Data Products’ concept and walk through the practical implementation of a production-grade analytics system with dbt as the backbone. The learnings will apply to data practitioners using dbt whether they're just getting started or working in a large enterprise.
by Mikkel Dengsøe, Co-Founder of SYNQ
Mikkel is the co-founder of Synq. Prior to Synq, he was leading data across operations and financial crime at UK fintech Monzo. Before that, he spent five years at Google working in data roles.

For Builders, by Builders: The Latest Tools from dbt Labs
In this meetup, we’ll dive into the latest tools and ideas we’ve been shipping — what they unlock, how they fit together, and why we built them the way we did.
This meetup is designed for builders, thinkers, and tinkerers — folks who want to roll up their sleeves (figuratively), learn from each other, and imagine what’s next for the analytics engineering stack.
Whether you’re curious about what’s new, want to see how others are approaching similar problems, or just want to ask hard questions — you’re in the right place.
by Bart van Delft, Solutions Architect, dbt Labs
Bart is from the Netherlands. With a passion for data dating back to 2014 when he wrote his master's thesis about the topic, Bart has since garnered experience in the field at companies like Snowflake and Oracle.

We are always looking for speakers!

To submit a session for one of the next meetups, please use our Sessionize page.
Are you in doubt if you're ready to give a talk? Check out dbt Labs's guide on how to deliver a fantastic presentation!

➡️ Join the dbt Slack community: https://www.getdbt.com/community/

🤝 For the best Meetup experience, make sure to join the #local-belgium channel in dbt Slack (https://slack.getdbt.com/)!

dbt is the standard in data transformation, used by over 50,000 organizations worldwide. Through the application of software engineering best practices like modularity, version control, testing, and documentation, dbt’s analytics engineering workflow helps teams work more efficiently to produce data the entire organization can trust.

Learn more: https://www.getdbt.com/