How to get Shopify data into Big Query

A beginners guide to options for getting your Shopify data into Google Big Query. Start here!

This article on RudderStack explains how to efficiently load data from Shopify into Google BigQuery for analysis. Here's a summary:

1. Data Extraction: Shopify's API provides over 35 endpoints to extract data like orders, products, and events. These can be filtered by parameters like creation dates to avoid duplicates.

2. Data Preparation: Extracted data must be converted to BigQuery-compatible formats (CSV or JSON) with supported data types like STRING, INTEGER, and TIMESTAMP.

3. Data Transfer Methods: Data can be loaded into BigQuery using Google Cloud Storage, direct POST requests to BigQuery, or streaming insert.

4. Automation: Tools like RudderStack simplify the process by integrating Shopify data with BigQuery without extensive coding or dealing with frequent API changes.

5. Implementation Flexibility: Depending on the use case, solutions range from manual uploads to automated pipelines via cloud tools and APIs.

For a detailed guide, you can refer to RudderStack's documentation here