> ## Documentation Index
> Fetch the complete documentation index at: https://shivamgoyal.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.
# Add Data to Database
> Learn how to add, import, and manage data in your CodeNull database
# Adding Data to Your Database
After creating your database, the next step is to populate it with data. CodeNull provides several methods to add and manage data in your database without writing complex database queries.
## Methods for Adding Data
Create records one at a time through the interface
Import data from CSV, Excel, JSON, or other formats
Generate sample data using AI for testing
Connect to external data sources via APIs
Create frontend forms that add data to your database
Transfer data from another database
## Manual Data Entry
The Data Explorer interface allows you to create individual records manually:
In your database dashboard, click on the collection or table where you want to add data.
Click the "Add Record" button in the top-right corner of the Data Explorer.
Complete the form with values for each field in your collection/table schema.
Click "Validate" to check for any errors, then "Save" to add the record to your database.
When entering data manually, you can use the "Clone" button to create similar records quickly. This is useful when adding multiple records with slight variations.
## Bulk Data Import
For adding multiple records at once, use the Bulk Import feature:
From your collection/table view, click "Import" in the toolbar.
Choose your data source:
* Upload a file (CSV, Excel, JSON)
* Paste data (JSON, CSV format)
* Connect to external source
Map the imported data fields to your database schema fields.
For each imported column, you can:
* Match to an existing field
* Transform data during import
* Skip certain columns
* Handle special data types (dates, geo coordinates, etc.)
Configure how to handle validation issues:
* Skip invalid records
* Attempt to fix common issues
* Stop import on any error
* Create a validation report
Click "Start Import" to begin the process. A progress indicator will show the status.
After import completes, review the summary showing:
* Number of records imported successfully
* Any validation issues encountered
* Fields that required transformation
## AI-Generated Test Data
CodeNull can generate realistic test data based on your schema:
From your collection/table view, click "Tools" → "Generate Test Data".
Set parameters for your test data:
* Number of records to generate
* Value ranges and patterns
* Relationships between records
* Scenarios to simulate (e.g., e-commerce transactions)
Review a sample of the data that will be generated and adjust settings as needed.
Click "Generate" to create the test data and add it to your database.
## Form-Based Data Collection
To collect data from users through your application:
Use the Frontend Dashboard to create a form component connected to your database.
Map form fields to database fields, including validation rules.
Configure what happens when the form is submitted:
* Direct database entry
* API processing before storage
* Email notifications
* Confirmation messages
Test the form to ensure data is correctly saved to your database.
## Managing Existing Data
CodeNull provides tools to work with your existing data:
### Data Explorer Interface
The Data Explorer allows you to:
* Browse records with filtering and sorting
* Edit individual field values
* Delete or archive records
* Export selected records
* View data relationships
### Batch Operations
Perform operations on multiple records at once:
* Update field values across many records
* Delete records matching certain criteria
* Export filtered data sets
* Run data transformations
To update a field across multiple records:
1. Use filters to select the target records
2. Click "Batch Update" in the toolbar
3. Select the field to update
4. Enter the new value or transformation rule
5. Preview changes before applying
6. Confirm to update all matching records
To delete records matching specific criteria:
1. Create a filter for the records to delete
2. Click "Batch Delete" in the toolbar
3. Review the affected records count
4. Choose between hard delete or soft delete (archive)
5. Confirm deletion with any required verification
## Best Practices
Start with a small set of test data to verify your schema design before importing large datasets.
* **Use descriptive IDs**: Create readable identifiers for important records
* **Validate before import**: Check data quality before adding to your database
* **Document data sources**: Track where your data came from for future reference
* **Test with realistic data**: Use data that resembles production use cases
* **Backup before bulk operations**: Create database backups before large data changes
## Next Steps
After adding data to your database, explore these next steps:
* [Design and optimize your database schema](/database-dashboard/schema-design)
* [Set up data migration workflows](/database-dashboard/data-migration)
* [Connect your database to frontend components](/frontend-dashboard/component-toolbox)