Data Engineering with dbt

linkedin.com/learning/data-engineering-with-dbt

22,288 learners | 1h 16m | Intermediate | Released Jan 2024 | 4.7/5 stars

Data Build Tool (dbt) has quickly become an essential tool in data stacks ranging from startups to big tech for managing data transformations. This course covers setting up, running, and managing a dbt project via the open-source dbt Core.

What You'll Learn

  • Install dbt Core and configure your environment
  • Create and manage a dbt project
  • Implement Medallion Architecture (Bronze, Silver, Gold layers)
  • Materialize dbt models
  • Write documentation as code
  • Build testing frameworks for data validation
  • Deploy dbt projects in production with GitHub Actions

Course Sections

  1. Environment preparation (coding & database)
  2. dbt project creation and configuration
  3. Building models and using ref functions
  4. Medallion Architecture
  5. Model materialization strategies
  6. Documentation and testing
  7. Multi-profile setup and GitHub workflow deployment
1 # Data Engineering with dbt
2
3 [linkedin.com/learning/data-engineering-with-dbt](https://www.linkedin.com/learning/data-engineering-with-dbt)
4
5 **22,288 learners** | 1h 16m | Intermediate | Released Jan 2024 | 4.7/5 stars
6
7 ---
8
9 Data Build Tool (dbt) has quickly become an essential tool in data stacks ranging from startups to big tech for managing data transformations. This course covers setting up, running, and managing a dbt project via the open-source dbt Core.
10
11 ## What You'll Learn
12
13 - Install dbt Core and configure your environment
14 - Create and manage a dbt project
15 - Implement Medallion Architecture (Bronze, Silver, Gold layers)
16 - Materialize dbt models
17 - Write documentation as code
18 - Build testing frameworks for data validation
19 - Deploy dbt projects in production with GitHub Actions
20
21 ## Course Sections
22
23 1. Environment preparation (coding & database)
24 2. dbt project creation and configuration
25 3. Building models and using ref functions
26 4. Medallion Architecture
27 5. Model materialization strategies
28 6. Documentation and testing
29 7. Multi-profile setup and GitHub workflow deployment

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