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Using dbt to manage your data warehouse
2025-11-05 · 18:45
Kobe Thuwis
– Data Engineer
@ Infofarm
In this twofold session, I'll cover how we've used dbt to bring order in heaps of SQL statements used to manage a datawarehouse. I'd like to share how dbt made our team more efficient and our data warehouse more resilient. Secondly, I'll highlight why dbt enabled a way forward on supporting low-code applications: by leveraging our data warehouse as a backend. I'll dive into systemic design, application architecture & data modelling. Tools/tech covered will be SQL, Trino, Outsystems, GIT, Airflow and of course dbt! Expect practical insights, architectural patterns, and lessons learned from a real-world implementation. |
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From chaos to control - how we scaled dbt for 150 analysts and engineers
2025-11-05 · 17:00
Mathias Lavaert
– Principal Data Engineer
@ DPG Media
Managing dbt for 150 analytics engineers meant evolving from fragmented dbt Core projects to unified standards, migrating to dbt Cloud. We solved security risks and inconsistent practices through standardization and centralized workflows, while maintaining our Airflow orchestration. Challenges remain in balancing governance with analyst autonomy at scale. |
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Fusion360
2025-11-05 · 17:00
Kaan Kizilirmak
– Data Engineer
@ IBA
Let's explore the capabilities of dbt's brand-new engine: Fusion. We’ll explore it from different angles, such as performance, functionalities, and how it transforms the developer experience. |
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Coalesce 2024: Transitioning from dbt Core to dbt Cloud: A user story
2024-10-16 · 20:28
Mathias Lavaert
– Principal Platform Engineer
@ DPG Media
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Alejandro Ivanez
– Platform Engineer
@ DPG Media
Join us as we share our journey of migrating from dbt Core to dbt Cloud. We'll discuss why we made this shift – focusing on security, ownership, and standardization. Starting with separate team-based projects on dbt Core, we moved towards a unified structure, and eventually embraced dbt Cloud. Now, all teams follow a common structure and standardized requirements, ensuring better security and collaboration. In our session, we'll explore how we improved our data analytics processes by migrating from dbt Core to dbt Cloud. Initially, each team had its way of working on dbt Core, leading to security risks and inconsistent practices. To address this, we transitioned to a more unified approach on dbt Core. This year we migrated dbt Cloud, which allowed us to centralize our data analytics workflows, enhancing security and promoting collaboration. For scheduling we manage our own Airflow instance using AWS EKS. We use Datahub as data catalog. Key points: Enhanced Security: dbt Cloud provided robust security features, helping us safeguard our data pipelines. Ownership and Collaboration: With dbt Cloud, teams took ownership of their projects while collaborating more effectively. Standardization: We enforced standardized requirements across all projects, ensuring consistency and efficiency, using dbt-project-evaluator. Speakers: Alejandro Ivanez Platform Engineer DPG Media Mathias Lavaert Principal Platform Engineer DPG Media Read the blog to learn about the latest dbt Cloud features announced at Coalesce, designed to help organizations embrace analytics best practices at scale https://www.getdbt.com/blog/coalesce-2024-product-announcements |
Dbt Coalesce 2024 |