Modernize SQL Analytics with DBT
A core component of any good analytics solution is still a relational database. Learn about SQL and build pipelines using DBT.
Data PlatformData Products
intermediate
8h
Overview
A one-day course on SQL and dbt. You write SQL on Snowflake, then build a dbt project with models, materializations, macros, seeds, snapshots, tests, and documentation, so SQL pipelines get smaller and fit into an orchestrator.
What you'll cover
- ▸Projects, profiles, and adapters
- ▸Models, sources, refs, and the dbt DAG
- ▸Materializations: view, table, incremental, ephemeral
- ▸Macros and Jinja templating
- ▸Seeds and snapshots
- ▸Tests and documentation
What you'll be able to do
- ✓Start a dbt project and connect it to a warehouse
- ✓Write SQL transformations as dbt models
- ✓Pick the right materialization for a model
- ✓Factor reusable logic into macros
- ✓Add tests and documentation to a project
Tags
Analytics EngineeringData TransformationTestingdbtSQLData AnalyticsData Engineering
Prerequisites
- Basic SQL knowledge
