#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:

#🏠 Local Setup

• Stack: DuckDB + dbt Core
• Cost: Free
• → Get Started

#☁️ Cloud Setup

• 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

• DuckDB Troubleshooting Guide — If you're getting OOM errors during dbt build with DuckDB

#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.

• SQL refresher

#Homework

• 2026 Homework

#Community notes