Design a Dataflow Pipeline from MySQL to BigQuery

Move MySQL retail data into BigQuery using a repeatable batch ingestion pipeline with staging tables, merge logic, and watermarks.
GCP • Foundations • Beginner • Retail

Architecture Diagram

Build this project

  • Source code
  • Setup files
  • Architecture walkthrough
  • Implementation videos
  • Execution guidance
  • Support
Get Project Access

Included in Data0to1 Project Library

What this project solves

Retail applications store day-to-day data such as products, customers, orders, shipments, payments, inventory, returns, and refunds inside operational databases.

But this data should not always be used directly for reporting or analytics from the same application database. In real projects, data is usually moved into a central analytics platform first, so other teams and pipelines can safely use it.

In this pipeline, you will move retail data from MySQL into BigQuery, load it through staging tables, merge it into raw tables, and use watermarks to load only new or changed records.

What you’ll build

  • Set up a MySQL retail source database
  • Load MySQL tables into BigQuery staging tables
  • Merge staged data into raw BigQuery tables
  • Use watermarks to avoid full reloads
  • Run ingestion for multiple retail domains
  • Orchestrate the workflow using Cloud Composer
  • Validate the loaded data in BigQuery

How you’ll build it

  • Create the MySQL source database and retail tables
  • Use Dataflow to load MySQL data into BigQuery staging
  • Merge staged records into raw BigQuery tables
  • Track watermarks to pick only new or changed data
  • Orchestrate the full workflow using Cloud Composer

Tools you’ll use

Cloud SQL for MySQL • Dataflow • BigQuery • Cloud Composer • Apache Airflow • Google Cloud Storage • SQL

What you’ll walk away with

After completing this pipeline, you will be able to:

  1. Explain how batch ingestion works on GCP
  2. Move MySQL data into BigQuery using Dataflow
  3. Use staging and merge logic for repeatable loads
  4. Use watermarks to load only new or changed records
  5. Orchestrate and validate the pipeline using Cloud Composer and BigQuery

Ready to build this project?

Get access to the project code, setup files, architecture walkthrough, implementation videos, and support.

Get Project Access