dbt Canvas makes it simple for every data practitioner to contribute to a dbt project. Learn the foundational concepts of developing in Canvas, dbt's new visual editor, and the best practices of editing and creating dbt models. After this course, you will be able to: Create new dbt models and edit existing models in dbt Canvas Understand the different operators in Canvas Evaluate the underlying SQL produced by Canvas Prerequisites for this course include: Basic SQL understanding What to bring: You will need to bring your own laptop to complete the hands-on exercises. We will provide all the other sandbox environments for dbt and data platform. Duration: 2 hours Fee: $200 Trainings and certifications are not offered separately and must be purchased with a Coalesce pass Trainings and certifications are not available for Coalesce Online passes

Get certified at Coalesce! Choose from two certification exams: The dbt Analytics Engineering Certification Exam is designed to evaluate your ability to: Build, test, and maintain models to make data accessible to others Use dbt to apply engineering principles to analytics infrastructure We recommend that you have at least SQL proficiency and have had 6+ months of experience working in dbt (self-hosted dbt or the dbt platform) before attempting the exam. The dbt Architect Certification Exam assesses your ability to: Design secure, scalable dbt implementations, with a focus on environment orchestration Role-based access control Integrations with other tools Collaborative development workflows aligned with best practices What to expect Your purchase includes sitting for one attempt at one of the two in-person exams at Coalesce You will let the proctor know which certification you are sitting for Please arrive on time, this is a closed-door certification, and attendees will not be let in after the doors are closed What to bring You will need to bring your own laptop to take the exam Duration: 2 Hours Fee: $100 Trainings and certifications are not offered separately and must be purchased with a Coalesce pass Trainings and certifications are not available for Coalesce Online passes If you no-show your certification, you will not be refunded

This is the introductory course for developers jumping into dbt! We will dive into data modeling, sources, data tests, documentation, and deployment. As an instructor-led course, you’ll have the chance to learn with peers, ask questions, and get live coaching and feedback. After this course, you will be able to: Explain the foundational concepts of dbt Build data models and a DAG to visualize dependencies Configure tests and add documentation to your models Deploy your dbt project to refresh data models on a schedule Prerequisites for this course: Intermediate SQL knowledge What to bring: You must bring your own laptop to complete the hands-on exercises. We will provide all the other sandbox environments for dbt and data platform. Duration: 4 hours Fee: $400 Trainings and certifications are not offered separately and must be purchased with a Coalesce pass Trainings and certifications are not available for Coalesce Online passes

Partner Summit is for dbt Labs Partners only Join us for an exclusive partner-focused event where you’ll gain insights into dbt’s strategic vision, discover new growth opportunities, and connect directly with the team driving ecosystem innovation. Be the first to hear the latest product and company updates, explore the role of dbt in AI-driven initiatives, and learn how our evolving partner programs will help you build your business with dbt.

Get certified at Coalesce! Choose from two certification exams: The dbt Analytics Engineering Certification Exam is designed to evaluate your ability to: Build, test, and maintain models to make data accessible to others Use dbt to apply engineering principles to analytics infrastructure We recommend that you have at least SQL proficiency and have had 6+ months of experience working in dbt (self-hosted dbt or the dbt platform) before attempting the exam. The dbt Architect Certification Exam assesses your ability to: Design secure, scalable dbt implementations, with a focus on environment orchestration Role-based access control Integrations with other tools Collaborative development workflows aligned with best practices What to expect Your purchase includes sitting for one attempt at one of the two in-person exams at Coalesce You will let the proctor know which certification you are sitting for Please arrive on time, this is a closed-door certification, and attendees will not be let in after the doors are closed What to bring You will need to bring your own laptop to take the exam Duration: 2 Hours Fee: $100 Trainings and certifications are not offered separately and must be purchased with a Coalesce pass Trainings and certifications are not available for Coalesce Online passes If you no-show your certification, you will not be refunded

This is the introductory course for dbt Architects. Learn foundational concepts covered in the dbt Architect exam including setting up dbt projects according to best practices, manage dbt connections and environments, and leverage dbt features to enhance security, observability and cross-department collaborations After this course, you will be able to: Explain how dbt integrates with data platforms and git providers Configure environments for different git promotion strategies Manage a multi-project account in dbt. Prerequisites for this course include: dbt fundamentals What to Bring: You will need to bring your own laptop to complete the hands-on exercises. We will provide all the other sandbox environments for dbt and data platform. Duration: 4 hours Fee: $400 Trainings and certifications are not offered separately and must be purchased with a Coalesce pass Trainings and certifications are not available for Coalesce Online passes

Operating across multiple countries with many business units, Belron built a repeatable framework on Snowflake using the dbt Platform to prevent scaling chaos. This solution codifies the analytics development lifecycle (ADLC) through modular code, environments, CI/CD, and automated testing. This session will share reusable patterns for new rollouts and provide a practical decision framework for choosing between dbt Projects on Snowflake and the dbt Platform for enterprise control, including governance, cross-project mesh, and observability. You'll also learn about the adoption metrics Belron uses to measure success. You'll learn: reusable ADLC guardrails, a dbt product decision tree, and how standardization enables a sustainable mesh.

Learn how to efficiently scale and manage data engineering pipelines with Snowflake's latest native capabilities for transformations and orchestration with SQL, Python, and dbt Projects on Snowflake. Join us for new product and feature overviews, best practices, and live demos.

Migration réussie vers Snowflake, mise en place de dbt… mais comment s’assurer que la donnée reste fiable au quotidien ? Avec Sifflet, l’équipe data d’ETAM a déployé une observabilité intelligente : détection d’anomalies, monitoring automatisé, intégration GitHub. Venez découvrir comment une petite équipe supervise à grande échelle et gagne en sérénité.

Découvrez comment Stellantis a relevé le défi de la qualité des données à grande échelle. Après la fusion de PSA et FCA, le constructeur a mis en place une Modern Data Stack (Snowflake, dltHub et dbt) pour unifier ses données et en garantir l'excellence.Vous plongerez dans l'architecture technique mise en oeuvre et vous découvrirez l'impact concret de ce projet sur des cas d'usage clés, tels que l'optimisation de la chaîne logistique et la réduction des coûts. Une opportunité unique de découvrir les meilleures pratiques et les enseignements tirés d'un projet de cette envergure.

La création et la gestion de pipelines de transformation de données peuvent être complexes et coûteuses. Dans cette session, apprenez à utiliser l'automatisation et les services gérés de Snowflake pour simplifier le développement, réduire les frais généraux d'infrastructure et améliorer le débugage avec la télémétrie intégrée. Découvrez les meilleures pratiques pour créer des pipelines évolutifs et rentables – et laissez votre équipe se concentrer sur les informations, et non sur la maintenance.

It's all about acquisitions, acquisitions, acquisitions! Matt Housley joins me to tackle the biggest rumor in the data world this week: the potential acquisition of dbt Labs by Fivetran. This news sparks a wide-ranging discussion on the inevitable consolidation of the Modern Data Stack, a trend we predicted as the era of zero-interest-rate policy ended. We also talk about financial pressures, vendor exposure to the rise of AI, the future of data tooling, and more.

Un témoignage inspirant pour les entreprises souhaitant moderniser leur stack ETL et exploiter pleinement les avantages du cloud.

MACIF partage son retour d'expérience sur la migration de plus de 400 workflows Informatica vers BigQuery et la plateforme dbt, en utilisant les accélérateurs développés par Infinite Lambda, dans le cadre de son projet de modernisation data "Move to Cloud". 

Aux côtés de Laurent, découvrez comment la MACIF a tiré parti du cloud pour accélérer la livraison de ses data products, réduire les risques techniques et améliorer la gouvernance des données.

Evgenii, platform engineer at a global pharmaceutical company invites you to explore the journey in building a cloud-native Federated Data Platform powered by dbt Cloud, Snowflake, and Data Mesh principles. Learn how we defined foundational tools and standards, and how we enabled automation and self-service to empower teams across the organization.

Les entreprises font face à une explosion des données, dispersées dans des systèmes cloisonnés qui

freinent l’efficacité et l’innovation. La centralisation des données change la donne : en créant une source

unique de vérité, elle permet d’exploiter tout le potentiel des données, de générer des insights

actionnables et de soutenir l’IA et la prise de décision stratégique.

Dans cette session, vous découvrirez :

● Les défis des données fragmentées et verrouillées

● Comment la centralisation accélère l’efficacité opérationnelle et l’innovation

● Une démonstration live intégrant Fivetran, dbt et Census pour illustrer la synchronisation des

données et le lead scoring dans Salesforce, le tout en moins de dix minutes

Selecting a suitable and high performing target group for CRM initiatives—such as newsletters and coupons—often involves time-consuming, manual coordination across multiple teams. In this session, we will demonstrate how we leveraged the combined strengths of Snowpark, Streamlit, and dbt to build a self-service application that allows CRM managers to define target groups independently—without relying on analytics resources. 

Our solution delivers real-time feedback based on user input, dramatically reducing turnaround times and simplifying the targeting workflow. We will explore how Snowpark acts as a seamless bridge between Streamlit and Snowflake, enabling efficient, in-database processing. Meanwhile, dbt ensures data consistency and reusability through standardized data products. 

Join us to discover how this integrated approach accelerates decision-making, ensures data governance, and unlocks scalable, self-service capabilities for your CRM teams.

Master the art of data transformation with the second edition of this trusted guide to dbt. Building on the foundation of the first edition, this updated volume offers a deeper, more comprehensive exploration of dbt’s capabilities—whether you're new to the tool or looking to sharpen your skills. It dives into the latest features and techniques, equipping you with the tools to create scalable, maintainable, and production-ready data transformation pipelines. Unlocking dbt, Second Edition introduces key advancements, including the semantic layer, which allows you to define and manage metrics at scale, and dbt Mesh, empowering organizations to orchestrate decentralized data workflows with confidence. You’ll also explore more advanced testing capabilities, expanded CI/CD and deployment strategies, and enhancements in documentation—such as the newly introduced dbt Catalog. As in the first edition, you’ll learn how to harness dbt’s power to transform raw data into actionable insights, while incorporating software engineering best practices like code reusability, version control, and automated testing. From configuring projects with the dbt Platform or open source dbt to mastering advanced transformations using SQL and Jinja, this book provides everything you need to tackle real-world challenges effectively. What You Will Learn Understand dbt and its role in the modern data stack Set up projects using both the cloud-hosted dbt Platform and open source project Connect dbt projects to cloud data warehouses Build scalable models in SQL and Python Configure development, testing, and production environments Capture reusable logic with Jinja macros Incorporate version control with your data transformation code Seamlessly connect your projects using dbt Mesh Build and manage a semantic layer using dbt Deploy dbt using CI/CD best practices Who This Book Is For Current and aspiring data professionals, including architects, developers, analysts, engineers, data scientists, and consultants who are beginning the journey of using dbt as part of their data pipeline’s transformation layer. Readers should have a foundational knowledge of writing basic SQL statements, development best practices, and working with data in an analytical context such as a data warehouse.

At PyData Berlin, community members and industry voices highlighted how AI and data tooling are evolving across knowledge graphs, MLOps, small-model fine-tuning, explainability, and developer advocacy.

• Igor Kvachenok (Leuphana University / ProKube) combined knowledge graphs with LLMs for structured data extraction in the polymer industry, and noted how MLOps is shifting toward LLM-focused workflows.
• Selim Nowicki (Distill Labs) introduced a platform that uses knowledge distillation to fine-tune smaller models efficiently, making model specialization faster and more accessible.
• Gülsah Durmaz (Architect & Developer) shared her transition from architecture to coding, creating Python tools for design automation and volunteering with PyData through PyLadies.
• Yashasvi Misra (Pure Storage) spoke on explainable AI, stressing accountability and compliance, and shared her perspective as both a data engineer and active Python community organizer.
• Mehdi Ouazza (MotherDuck) reflected on developer advocacy through video, workshops, and branding, showing how creative communication boosts adoption of open-source tools like DuckDB.

Igor Kvachenok Master’s student in Data Science at Leuphana University of Lüneburg, writing a thesis on LLM-enhanced data extraction for the polymer industry. Builds RDF knowledge graphs from semi-structured documents and works at ProKube on MLOps platforms powered by Kubeflow and Kubernetes.

Connect: https://www.linkedin.com/in/igor-kvachenok/

Selim Nowicki Founder of Distill Labs, a startup making small-model fine-tuning simple and fast with knowledge distillation. Previously led data teams at Berlin startups like Delivery Hero, Trade Republic, and Tier Mobility. Sees parallels between today’s ML tooling and dbt’s impact on analytics.

Connect: https://www.linkedin.com/in/selim-nowicki/

Gülsah Durmaz Architect turned developer, creating Python-based tools for architectural design automation with Rhino and Grasshopper. Active in PyLadies and a volunteer at PyData Berlin, she values the community for networking and learning, and aims to bring ML into architecture workflows.

Connect: https://www.linkedin.com/in/gulsah-durmaz/

Yashasvi (Yashi) Misra Data Engineer at Pure Storage, community organizer with PyLadies India, PyCon India, and Women Techmakers. Advocates for inclusive spaces in tech and speaks on explainable AI, bridging her day-to-day in data engineering with her passion for ethical ML.

Connect: https://www.linkedin.com/in/misrayashasvi/

Mehdi Ouazza Developer Advocate at MotherDuck, formerly a data engineer, now focused on building community and education around DuckDB. Runs popular YouTube channels ("mehdio DataTV" and "MotherDuck") and delivered a hands-on workshop at PyData Berlin. Blends technical clarity with creative storytelling.

Connect: https://www.linkedin.com/in/mehd-io/

When Virgin Media and O2 merged, they faced the challenge of unifying thousands of pipelines and platforms while keeping 25 million customers connected. Victor Rivero, Head of Data Governance & Quality, shares how his team is transforming his data estate into a trusted source of truth by embedding Monte Carlo’s Data + AI Observability across BigQuery, Atlan, dbt, and Tableau. Learn how they've begun their journey to cut data downtime, enforced reliability dimensions, and measured success while creating a scalable blueprint for enterprise observability.