Automate BigQuery Exports to Cloud Storage

Export business-ready customer and order datasets from BigQuery to Cloud Storage as CSV/Parquet files with delivery tracking and Composer orchestration.

GCP • Analytics • Intermediate • Retail

Architecture Diagram

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What this project solves

Analytics data is not always consumed inside BigQuery.

Business teams may need customer segments for campaigns, operations teams may need recent order files, and external systems may need periodic data exports to stay updated.

In this pipeline, you will automate BigQuery exports to Cloud Storage. You will generate CSV and Parquet files from business-ready datasets, track every delivery, archive exported files, and orchestrate the full export workflow using Cloud Composer.

What you’ll build

Export customer and order datasets from BigQuery
Generate CSV and Parquet files for downstream consumers
Create reusable export definitions
Deliver business datasets to Cloud Storage
Track every export with audit history
Archive exported files for future reference
Orchestrate export workflows using Cloud Composer

How you’ll build it

Prepare reusable BigQuery export views
Generate export files from analytics marts
Write exported files to the Cloud Storage outbox
Track successful and failed export deliveries
Archive delivered files and validate export output

Tools you’ll use

BigQuery • Google Cloud Storage • Cloud Composer • Apache Airflow

What you’ll walk away with

After completing this pipeline, you will be able to:

Build export pipelines from BigQuery analytics marts
Generate business-ready datasets for downstream consumers
Deliver curated files through Cloud Storage
Track export history and delivery status
Orchestrate and validate reverse ETL workflows on GCP

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