
dbt on Databricks
>_ What You'll Learn
- Gain hands-on experience with dbt Cloud and dbt Core, including setup, orchestration, and deployment in real-world scenarios.
- Understand and implement dbt models, sources, and seeds within Databricks for efficient data transformations.
- Learn to use Jinja functions and macros to create dynamic, reusable SQL code in dbt projects.
- Master table materializations and incremental data loading to optimize data workflows and performance.
- Develop comprehensive testing and documentation practices to ensure data quality and project transparency in dbt.
>_ Requirements
- Solid Understanding of Databricks, including Lakehouse Architecture
- Familiarity with SQL
- Knowledge of Cloud Computing (either Azure, GCP or AWS)
- Access to Cloud Platform Account (either Azure, GCP or AWS)
- Awareness of Version Control (Optional)
/ Course Details & Curriculum
- Introduction to dbt and Key Concepts: Begin with an in-depth overview of dbt, Jinja templating, and YAML for configuration. Understand how these tools come together to streamline data transformation.
- Setting Up the Environment: Follow step-by-step guidance on configuring dbt Cloud with Databricks, version control essentials, and an introduction to core components and data pipelines.
- Data Modeling and Transformations: Explore multi-layer data architecture, including Bronze, Silver, and Gold models. Learn practical approaches for source referencing, schema configuration, and building efficient data pipelines using dbt commands.
- Advanced Testing and Validation: Implement robust data quality checks through generic and singular tests, transitioning from tests: syntax to data_tests:, and integrate dbt packages like dbt_utils for enhanced functionality.
- Jinja, Macros, and Custom Functions: Master the art of reusable, scalable code with Jinja syntax and macros. Gain the skills to manipulate data models dynamically, change schemas, and develop custom logic for specific use cases.
- Materializations Explained: Understand various materialization strategies including tables, views, incremental loads, and snapshots. Delve into specific scenarios like SCD Type 2 for dimension tables and incremental updates for fact tables.
- Deployment and Production Workflows: Set up a production-ready dbt environment on Databricks, manage jobs, and deploy models seamlessly. Learn to configure environment and target variables for streamlined CI/CD workflows.
- Developing with dbt Core: Experience the flexibility of dbt Core through local project setups, GitHub integration, and command-line navigation, while learning best practices for version control and collaboration.
- Troubleshooting and Advanced Techniques: Gain insights into handling common connection issues, optimizing project performance, and scaling workloads on Databricks.
Author and Instructor
Malvik Vaghadia
Expert at Udemy
With years of hands-on experience in Development, Malvik Vaghadia has dedicated thousands of hours to teaching and mentorship. This course is the culmination of industry best practices and a proven curriculum that has helped thousands of students transition into professional roles.
Community Feedback
Michael Chen
Verified Enrollment
"This dbt on Databricks course was exactly what I needed. The instructor explains complex Development concepts clearly. Highly recommended!"
Sarah Johnson
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"I've taken many Udemy courses on Development, but this one stands out. The practical examples helped me land a job."
David Smith
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"Great value for money. The section on dbt (Data Build Tool) was particularly helpful."
Emily Davis
Verified Enrollment
"Excellent structure and pacing. I went from zero to hero in Development thanks to this course. Lifetime access is a huge plus."
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