Connect Shopify to BigQuery

Why Connect Shopify to BigQuery?

Here are some reasons why this integration is valuable:

1. Centralized Data Storage

BigQuery serves as a centralized data warehouse, allowing businesses to store and manage data from various sources in one place. By connecting Shopify to BigQuery, businesses can consolidate their e-commerce data alongside other relevant datasets.

As businesses grow and their data volume increases, BigQuery provides the scalability and performance required to handle large datasets and complex queries.

2. Comprehensive Data Analysis

Shopify provides valuable data on sales, orders, products, customers, and more. By loading Shopify data into BigQuery, businesses can combine it with data from other sources such as marketing platforms, CRM systems, or advertising channels.

3. Data Backup and Disaster Recovery

Keeping a backup of Shopify data in Google BigQuery provides an additional layer of data protection. In the event of a Shopify outage or data loss, businesses can rely on their BigQuery backup to ensure their e-commerce data remains accessible and secure.

4. Advanced Analytics and Reporting

BigQuery offers advanced querying and analytical capabilities, enabling businesses to perform in-depth analysis on their Shopify data. By leveraging BigQuery’s features, businesses can uncover valuable insights, track key metrics, and create custom reports and visualizations.

5. Integration with Business Intelligence Tools

Loading data from Shopify into BigQuery allows businesses to seamlessly integrate with various BI tools such as Tableau, Power BI, or Looker Studio. This integration enables businesses to create interactive dashboards, perform complex analyses, and visualize their e-commerce data effectively.

Connect Shopify to Google BigQuery

It is very simple to connect Shopify to Google BigQuery, it can be done in a fast and easy manner with Windsor.ai.

First Step:

Register or log in if you already have an account.

You need to select Shopify as a Data Source and Grant Access to Windsor.ai.

And then you can click on “Shopify App Store”. Than you paste your store URL in here:

Click on grant access and then your app will be installed. In case you are an agency or you have multiple stores, you can repeat that process as many time as you want.

Second Step:

Once you select the data source, click the “Preview and Destination” Button. 

Select BigQuery by clicking on the logo, as shown in the screenshot below.  

Third Step:

Once you select BigQuery, click the Add Destination Task Button and fill out necessary fields . 

Fourth Step:

In the final step, grant access to the user: bq-upload@windsor-ai-bigquery.iam.gserviceaccount.com. That’s all!

Once you go through these steps, you will see that the data is automatically populated into your BigQuery account.

Note: As a connector URL, you can use any URL providing a JSON. Either from the connectors or for example a URL with cached and transformed data.

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Which data can be transferred from Shopify to BigQuery?

When integrating Shopify with BigQuery, you can move a variety of data from Shopify to BigQuery to analyze and work with. Here are some examples of the data you can move:

1. Orders: Information about orders placed on your Shopify store, including order ID, customer details, order status, order total, shipping information, and more.
2. Products: Data related to the products available in your Shopify store, such as product details, variants, prices, inventory levels, and product categories.
3. Customers: Customer data, including customer names, contact information, purchase history, customer tags, and customer segments.
4. Discounts and Coupons: Data about discounts and coupons applied to orders, including discount codes, amounts, usage statistics, and associated orders.
5. Refunds: Information on customer refunds, including refund amounts, refund reasons, and associated orders.
6. Abandoned Checkouts: Data related to abandoned checkouts, including customer information, abandoned cart contents, and reasons for abandonment.
7. Analytics and Traffic Data: Shopify provides data on website visits, traffic sources, conversion rates, and other analytics metrics.
8. Fulfillment and Shipping: Data about shipping and fulfillment, including carrier information, tracking numbers, shipping costs, and delivery status.

The Shopify API provides access to a wide range of data, allowing you to extract and load the relevant data into BigQuery for analysis and reporting.

What are the Format Requirements for Data before Exporting from Shopify to BigQuery?

Before initiating the data transfer from Shopify to BigQuery, it’s crucial to ensure that the data is in a format compatible with BigQuery. For instance, if the API you are utilizing returns data in XML, it must be converted to a serialization format that BigQuery can comprehend. Currently, BigQuery supports two data formats:

1. CSV
2. JSON

Additionally, it is essential to confirm that the data types being used align with those supported by BigQuery, which include:

• STRING
• BOOLEAN
• INTEGER
• FLOAT
• TIMESTAMP
• RECORD

Try Windsor.ai today

Access all your data from your favorite sources in one place.
Get started for free with a 30 - day trial.

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