Data Import
A guide to importing data from various sources into BijouCore entities, with a focus on CSV import capabilities.
📄 Overview
Data Import allows you to bring external data into your BijouCore entities. This capability is essential for migrating from legacy systems, integrating with third-party data sources, or bulk loading initial data sets.
The platform provides a flexible, configurable approach to importing data, with support for different file formats, validation rules, and mapping configurations. This ensures that imported data maintains integrity and conforms to your entity requirements.
⚙️ CSV Import
CSV (Comma-Separated Values) is a widely used format for data exchange, and BijouCore provides comprehensive support for importing CSV files into your entities.
Basic Process
The CSV import process follows these general steps:
- Create or select an import configuration for your target entity
- Upload and preview your CSV file
- Map CSV columns to entity fields
- Configure import options
- Run the import and review results
Import Configurations
Import configurations store your settings for repeated use, including column mappings, import modes, and validation rules.
Property | Description |
---|---|
Name | Unique identifier for the import configuration |
Description | Optional descriptive text explaining the purpose of this configuration |
Target Entity | The entity where data will be imported |
Access Permissions | Roles that can use this import configuration |
CSV Settings
Configure how your CSV file should be parsed:
Setting | Description |
---|---|
Delimiter | Character that separates values (comma, semicolon, tab, pipe) |
Has Header Row | Whether the first row contains column names |
Skip Rows | Number of rows to skip at the beginning |
Encoding | Character encoding used in the file (UTF-8, ASCII, etc.) |
Culture Info | Regional settings for parsing dates and numbers |
Advanced Options | Quote character, line terminators, comment handling, etc. |
Import Modes
Control how imported data interacts with existing records:
Mode | Description |
---|---|
Create New | Only insert new records, do not update existing ones |
Update Existing | Only update existing records based on key fields, do not create new ones |
Create or Update | Update existing records if found, otherwise create new ones |
Delete | Delete records that match the key fields |
Synchronize | Make the target entity match the source data (create, update, delete as needed) |
Column Mappings
Map your CSV columns to entity fields with these options:
Property | Description |
---|---|
CSV Column | The column name from your CSV file |
Entity Field | The target field in your entity |
Is Key Field | Fields used to identify existing records for update/delete operations |
Required | Whether the field must contain a value |
Note: When creating a new entity, you can quickly generate fields from your CSV columns. This is useful for rapid prototyping or when designing entities based on existing data structures.
📊 Import Processing
Validation
During import, data is validated to ensure it meets your entity's requirements:
- Field data types must match (e.g., dates, numbers, boolean values)
- Required fields must have values
- String length limits are enforced
- Entity validation rules are applied
- Records with validation errors are logged but not imported
Import Job History
Each import operation is tracked as a job with:
- Date and time of execution
- User who initiated the import
- Number of records processed
- Success/failure statistics
- Detailed error logs for troubleshooting
Best Practices
- Always back up your data before running large imports
- Test imports with a small sample of your data first
- Use descriptive configuration names that indicate the data source and purpose
- Define key fields wisely for update operations
- Check error logs after import to identify and fix data issues
- Consider breaking very large datasets into multiple smaller imports