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README.md

Module 4: Analytics Engineering

Goal: Transforming the data loaded in DWH into Analytical Views developing a dbt project.

Prerequisites

The prerequisites depend on which setup path you choose:

For Cloud Setup (BigQuery):

  • Completed Module 3: Data Warehouse with:
    • A GCP project with BigQuery enabled
    • Service account with BigQuery permissions
    • NYC taxi data loaded into BigQuery (yellow and green taxi data for 2019-2020)

For Local Setup (DuckDB):

  • No prerequisites! The local setup guide will walk you through downloading and loading the data.

Note

This module focuses on yellow and green taxi data (2019-2020). While Module 3 may have included FHV data, it is not used in this dbt project.

Setting up your environment

Choose your setup path:

  • Stack: BigQuery + dbt Cloud
  • Cost: Free tier available (dbt Cloud Developer), BigQuery costs vary
  • Requires: Completed Module 3 with BigQuery data
  • → Get Started

Content

Introduction to Analytics Engineering

Introduction to data modeling

What is dbt?

Differences between dbt Core and dbt Cloud

Project Setup

Alternative A Alternative B
BigQuery + dbt Platform DuckDB + dbt core

dbt Course

dbt Project Structure dbt Sources dbt Models Seeds and Macros
dbt Tests Documentation dbt Packages dbt Commands

Troubleshooting

Extra resources

Note

If you find the videos above overwhelming, we recommend completing the dbt Fundamentals course and then rewatching the module. It provides a solid foundation for all the key concepts you need in this module.

SQL refresher

The homework for this module focuses heavily on window functions and CTEs. If you need a refresher on these topics, you can refer to these notes.

Homework

Community notes

Did you take notes? You can share them here