
The Complete Snowflake & dbt Hands-On Course
udemy · IT y software · ⭐ 4.64 (1.351 reseñas) · All Levels · en · ⏱ 12 h
Impartido por Daniel Weigel · 13.165 alumnos
19.99 USD
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Descripción
Want to build real, production-ready data pipelines with two of the most in-demand tools in the modern data stack ? This all-levels, project-based course takes you from the basics to advanced workflows with Snowflake and dbt (data build tool). With over 11 hours of content, you’ll not just learn the concepts — you’ll apply them step by step in real projects, including a Bitcoin blockchain data pipeline designed to mirror real-world challenges. In this course, you will: • Set up and manage Snowflake environments (databases, schemas, stages). • Ingest data from local files, S3 buckets, and external sources. • Write modular SQL with dbt models, CTEs, and window functions. • Apply ELT best practices and build maintainable data models. • Use dbt contracts, versioning, and generic tests for reliability. • Set up CI/CD with GitHub Actions and key pair authentication. • Optimize Snowflake with caching, micropartitions, and clustering. • Prepare data for analytics tools like Power BI. This course is packed with real-world use cases, code walkthroughs, and tips I’ve implemented in production environments. By the end, you’ll be confident in building scalable, maintainable data pipelines — skills you can immediately apply in your current role or future projects. These lessons are designed to give you both technical expertise and practical confidence when working with modern data tools.
Lo que aprenderás
- Ingest data into Snowflake from multiple sources (AWS S3 and local files)
- Set up and manage internal and external stages in Snowflake
- Use SnowSQL to load and query data in Snowflake efficiently
- Build and optimize data transformation models using dbt
- Understand version control and modularity in dbt for scalable data projects
- Work with semi-structured data - JSON
- Work with Time functions and Window functions
Requisitos
- Basic SQL knowledge is recommended but not required
- Familiarity with data concepts (optional, but helpful)
- No prior experience with dbt or Snowflake required - everything will be explained step by step