Free template: combine and join tables from your CSV data
Combine and join tables from your CSV 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 uploading your CSV files.
- Select the specific tables you want to join from your CSV files. Configure any necessary data formatting or filtering.
- 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 set up, this process will handle new CSV files automatically.
How to use CSV data with Parabola
Parabola makes working with CSV files intuitive and efficient through its drag-and-drop interface and powerful data transformation capabilities.
- Import multiple CSV files simultaneously for batch processing
- Automatically detect column headers and data types
- Preview data as you build your Flow to ensure accuracy
- Transform and combine data without writing any code
- Export results in various formats including CSV, Excel, or direct to other platforms
Retrieving data from CSV
In Parabola, retrieving data from CSV files is straightforward and flexible. The platform automatically handles different CSV formats and allows you to import data from various sources, including cloud storage and local files.
Key features
- Automatic column type detection
- Support for different delimiter types
- Handling of escaped characters and special formatting
- Multiple file import capabilities
- Error handling and validation
How to use
- Add the Pull from CSV step to your Flow
- Select your CSV file source
- Configure column settings if needed
- Preview your data to ensure correct formatting
- Connect to subsequent steps for further processing
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 data enrichment
Combine customer transaction data from one CSV with demographic information from another to create comprehensive customer profiles. This enables better targeting and personalization in marketing campaigns.
Inventory management
Merge product inventory data with supplier information to track stock levels, costs, and supplier relationships in a single view. This helps optimize ordering and maintain appropriate stock levels.
Sales performance analysis
Join sales data with employee information to analyze performance metrics across different regions, teams, and time periods. This provides valuable insights for management decisions and resource allocation.
Working with CSV data in Parabola provides a powerful way to combine and transform your data without the complexity of traditional programming. By following these steps and examples, you can efficiently merge your CSV tables and create meaningful insights for your business needs.
