Simplifying data pipelines using dbt

In the past, the bridge between raw data and business insights was a "black box" of custom code, hard-to-maintain scripts, and broken pipelines. Today, the Modern Data Stack has changed the rules. This course is a hands-on journey through the entire Data Engineering Lifecycle, focused on making the most complex stage—Transformation—the simplest part of your day using dbt (Data Build Tool).

We don't just talk about theory. We build. We start with raw e-commerce data in MongoDB, move it into a PostgreSQL warehouse via Fivetran, and then use dbt to turn that raw noise into high-value, analytics-ready tables for Looker Studio.

What makes this course different?

We focus on simplicity. You will see how dbt allows you to apply software engineering best practices—like version control, testing, and documentation—using nothing but the SQL you already know.

What You Will Learn:

• The Big Picture: Navigate the full lifecycle from Data Generation (OLTP) to Consumption (OLAP/BI).

• Automated Ingestion: Master hands-off data syncing from MongoDB to PostgreSQL.

• dbt Core Mastery: Learn to build modular, reusable SQL models that stay organized as your project grows.

• Professional Visualization: Deliver your transformed data to stakeholders using Looker Studio.

Who is this for?

• Aspiring Data Engineers who want to master the industry-standard tool for transformation.

• Data Analysts looking to move "upstream" and take control of the data modeling process.

• SQL Users tired of "spaghetti code" stored procedures who want a cleaner, more professional workflow.

By the end of this course, you’ll have a portfolio-ready project that proves you can architect a modern, scalable, and—most importantly—simple data pipeline from scratch.