Easy, fast, and scalable: pick 3. MotherDuck’s managed DuckLake data lakehouse blends the cost efficiency, scale, and openness of a lakehouse with the speed of a warehouse for truly joyful dbt pipelines. We will show you how!

Structured Query Language (or SQL for short) is a programming language to manage data in a database system and an essential part of any data engineer’s tool kit. In this tutorial, you will learn how to use SQL to create databases, tables, insert data into them and extract, filter, join data or make calculations using queries. We will use DuckDB, a new open source embedded in-process database system that combines cutting edge database research with dataframe-inspired ease of use. DuckDB is only a pip install away (with zero dependencies), and runs right on your laptop. You will learn how to use DuckDB with your existing Python tools like Pandas, Polars, and Ibis to simplify and speed up your pipelines. Lastly, you will learn how to use SQL to create fast, interactive data visualizations, and how to teach your data how to fly and share it via the Cloud.

Discover how to cut complexity of your dbt data pipelines with serverless DuckDB while improving performance and drastically reducing costs. This session covers practical strategies for cutting complexity and expenses in data flows while enjoying a more ergonomic and frictionless workflow. Learn how adopting a DuckDB-based architecture can streamline your operations, enhance developer experience, and boost efficiency.

Speaker: Alex Monahan Forward Deployed Software Engineer MotherDuck

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