Udemy – Dataform Zero to Hero: Master Enterprise-Level Analytics

This course teaches you how to build clean, modular, and scalable analytics pipelines using Dataform on BigQuery. It’s the same workflow used by modern analytics teams at scale.

You’ll start by learning what modular analytics actually means and why it matters. Then, you’ll build a fully version-controlled pipeline using SQLX, GitHub, and BigQuery — from source to reporting layer.

We’ll guide you through modeling patterns, directory structures, tagging strategies, assertions, and release scheduling. You’ll write models using ref(), build a full funnel report, validate data quality, and trigger scheduled runs from the main branch.

You’ll also learn how to:

• Connect GitHub to Dataform and structure branches for collaboration
• Use assertions for row count, primary key, and null checks
• Set up prod_ prefixes for your production tables
• Automatically refresh outputs on a release schedule
• Connect BigQuery to Power BI and optionally to VS Code notebooks for local development

By the end, you’ll have a complete analytics stack that’s clean, testable, repeatable — and built to scale.

If you’re a data analyst, analytics engineer, or job seeker preparing for a modern data role, this course will level up your workflow from static SQL to real production pipelines and modernize your entire approach to analytics.

Who this course is for:

• Data analysts who want to move beyond ad hoc SQL and start working with modular, production-ready code
• Analytics engineers and BI developers looking to adopt version control, reusable models, and scheduled pipelines
• Job seekers and career switchers preparing for roles in data or analytics engineering
• Team leads or managers who want to standardize their analytics workflows using modern best practices
• Whether you’re already in the field or leveling up for your next role, this course gives you the tools, patterns, and workflows used by high-performing enterprise teams.

DOWNLOAD LINK: Dataform Zero to Hero: Master Enterprise-Level Analytics