Madrid dbt Meetup #5 (in-person)

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, DataOps, modeling, testing, and team structures.

📍 Venue Host: Utopicus Habana (P.º de La Habana, 9, 11, 28036 Madrid)
🍕 Catering: Drinks & Pizza at the place of the event
🤝 Organizer: Astrafy is organizing this event, enabled by the community team at dbt Labs

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

🗓️Agenda:

• 18:45 - 19:00 | Welcome
• 19:00 - 19:20 | Data validation with dbt: Going beyond testing (Alejandro de la Cruz Lopez - Astrafy)
• 19:25 - 19:45 | How Airflow + dbt Work Together at Okta (Miquel Angel Andreu Febrer - Okta)
• 19:50 - 20:10 | Leveraging column-level lineage to scale your dbt projects (Benoit Perigaud - dbt)
• 20:15 - 22h00 | Networking with drinks & pizzas 🍺 🍕

🗣️Presentation #1:
dbt can be leveraged for more than just basic testing. We will dive into advanced data validation techniques that ensure data quality beyond conventional testing in dbt. We will use Recce as a new emerging tool that allows validation checks and improved approval requests.

Speaker bio: Alejandro de la Cruz López is an experienced Data Engineer with a strong background in Data Science and Artificial Intelligence. He has led various data projects, optimizing systems and improving infrastructure for several organizations. Alejandro holds multiple professional certifications and has authored articles on data engineering practices. His work focuses on delivering efficient, scalable data solutions in the cloud.

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🗣️Presentation #2:
In this presentation, Miquel Angel will show how Okta dynamically builds all dbt DAGs from upstream to downstream based on tags and the dbt project structure, automates tests inside the dags, and uses the same warehouse configuration for both dbt runs and tests.

Speaker bio: Data Engineer specialized in ETL, BigData processes, and DevOps

🗣️Presentation #3:
Today, we have tools to enforce quality checks on projects, at the model level, like dbt_project_evaluator. Those tools are indispensable to allow teams to scale their dbt transformation. But while we've been focusing on rules at the model level. Could we leverage CLL to also define rules at the column level now? The idea of this talk would be to build an open-source tool and present what problems it can solve.

Speaker bio: Staff Analytics Engineer at dbt Labs

➡️ Join the dbt Slack community: https://www.getdbt.com/community/
🤝For the best Meetup experience, make sure to join the #local-\ channel in dbt Slack (https://slack.getdbt.com/).
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dbt is the standard in data transformation, used by over 40,000 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/