Free template: combine and join tables from your Shopify data
Combine and join tables from your Shopify data without writing a single line of code.
The Parabola Team
Transform your data in five easy steps using Parabola's drag-and-drop interface, powered by AI.
- Set up your data source by creating a new Parabola flow and connecting your Shopify store. This creates your workflow foundation.
- Select the specific tables you want to join, such as orders, products, or customer data. Configure any necessary filters or parameters.
- Define your join conditions by identifying the common fields between tables. This ensures accurate data relationships.
- Use Parabola's transformation tools to create the join operations. This step lets you specify how tables should be combined and what information to include.
- Generate your results by previewing the joined data and running your automated flow. Once configured, this process will sync automatically.
How to use Shopify with Parabola
Parabola's Shopify integration enables seamless e-commerce data management and transformation.
- Import Shopify data automatically with scheduled refreshes
- Transform and clean ecommerce data with built-in steps
- Connect Shopify data with other business systems effortlessly
Retrieving data from Shopify
Connecting your Shopify store to Parabola is straightforward using the Pull from Shopify step. This integration allows you to access various data types from your store, including orders, products, customers, and inventory information.
Key features
- Direct API connection to your Shopify store
- Multiple data type selection options
- Customizable date ranges for data retrieval
- Automatic pagination handling
- Real-time data refresh capabilities
How to use
- Add the Pull from Shopify step to your Flow
- Connect your Shopify account to Parabola
- Select the desired data type (orders, products, etc.)
- Configure any additional parameters or filters
- Run the step to retrieve your data
Combine tables
The Combine tables step in Parabola allows you to merge data sets from different sources based on matching columns. This powerful feature enables you to create comprehensive views of your business data and perform advanced analytics – mirroring the functionality of a vlookup in Excel.
Key features
- Multiple joining methods (inner, left, right, full outer)
- Column matching flexibility
- Automatic data type handling
- Duplicate handling options
How to use
- Add the Combine tables step to your Flow
- Connect the two datasets you'd like to join to the Combine tables step
- Choose the join type
- Map the matching columns
- Specify whether you'd like to match where any values match or all values
- Update results to preview the output and make edits as necessary
Practical use cases and examples
Customer lifetime value analysis
Combine customer data with order history to calculate lifetime value metrics. This joined dataset enables you to identify your most valuable customers and analyze their purchasing patterns over time.
Inventory optimization
Merge product data with sales history to create a comprehensive view of inventory performance. This combination helps in predicting stock requirements and optimizing reorder points across different locations.
Marketing campaign effectiveness
Join customer demographic data with purchase history to evaluate marketing campaign performance. This unified view allows you to measure the success of targeted promotions and adjust strategies accordingly.
By leveraging Parabola's powerful combination capabilities with your Shopify data, you can create sophisticated analyses and automate complex workflows. The visual nature of Parabola's platform makes it accessible to users of all technical levels, while still providing the flexibility to handle complex data operations.
