
Learn dbt cloud from basics to advanced, transform data in the cloud, and manage test cases while deploying projects to production using simple sql statements.
Learn how to create a dbt Cloud account, set up a new project and schema, configure a database connection, and create and clone a private Git repository with deploy keys.
Define and run tests for the stock index model in a dbt cloud project, covering unique, not null, accepted values, and relationships; validate with test files and logs.
Define and test a macro under macros, creating a get_currency function to output a list of currencies. Build a model and write a select statement to verify the query results.
Learn to deploy and run dbt cloud projects in production by creating deployment environments, configuring branches and credentials, and executing jobs with seeds, snapshots, and tracking data lineage.
This course provides detailed lectures on dbt Cloud, applying transformations using Sql Statements, performing the test cases during development and deploying the project into Production environment.
Topics covered in the course are,
Models
Materializations
Tests
Variables
Sources
Seeds
Snapshots
Hooks
Jinja
Macros
Deployments
In detail the course includes, Introduction of Models and implementation, Materializations (Table, View, Incremental and Ephemeral) , Tests cases with various scenarios using schema.yml file as well as within Sources , creating Seeds and Sources, managing Snapshots, creating Hooks, utilizing Jinja and Macros, Deployment process, defining connection with AWS RDS PostgreSql instance, various methods to develop a model, referencing the models, deep understanding of dbt_project.yml and schema.yml files, reusability models and functions, efficient way of transformations using Sql, defining global and local variables, defining the variables during run time, interacting with PostgreSql, dynamic schema generation, dynamic, database object creation .etc,.
By the end of the course, you will have a proficient knowledge on dbt Cloud, transforming the data in a data warehouse using simple Sql statements, managing the test cases and deploying the project into production environment.
This course is meant for Data Engineers, ETL Architects, ETL Developers, Data Analysts, Data Scientists, BI Developers, Database Developers, Data Integration Specialists, Data Architects and whoever need to enhance their skill in the field of data engineering and analytics