Documentation Index
Fetch the complete documentation index at: https://docs.rowbase.com/llms.txt
Use this file to discover all available pages before exploring further.
Data Organization
Use Meaningful Names
Give your projects and datasets clear, descriptive names that your team will understand. Good examples:- “Q1 2024 Marketing Leads”
- “Customer Churn Analysis”
- “Product Inventory - US Warehouse”
- “Data1”
- “Test”
- “Final_v2_FINAL”
Structure Your Projects
Group related datasets into projects by:- Team or department - Marketing, Sales, Product
- Initiative - Product launch, Annual review
- Data source - CRM exports, Survey responses
Data Quality
Clean Data on Import
Address data quality issues early:- Remove duplicates - Deduplicate immediately after import using primary keys
- Standardize formats - Use operations to normalize dates, phone numbers, and addresses
- Handle nulls - Decide how to treat missing values before analysis
Set Primary Keys
Always designate primary keys for datasets that will be updated:- Enables reliable deduplication
- Supports upsert operations
- Maintains record identity across updates
Validate Your Data
Before sharing or exporting:- Check row counts match expectations
- Verify column types are correct
- Review a sample of transformed data
- Test filters return expected results
Operations Pipeline
Order Matters
Apply operations in a logical sequence:Filtering before deduplication ensures you keep the right records when duplicates exist.
Keep Pipelines Simple
- Each operation should do one thing well
- Avoid overly complex filter conditions
- Break large transformations into steps
- Name operations descriptively
Document Your Work
Add comments explaining:- Why an operation was applied
- Business logic behind filters
- Data source and freshness
- Known limitations or caveats
Collaboration
Use Appropriate Access Levels
| When to use | Access level |
|---|---|
| Working draft | Keep private |
| Team review | Share with editors |
| Stakeholder review | Share as view-only |
| External sharing | Use share links carefully |
Communicate Changes
When modifying shared datasets:- Notify teammates before major changes
- Document what changed and why
- Use comments for context
Review Before Sharing Externally
Before creating public links:- Verify no sensitive data is exposed
- Check that filters are applied correctly
- Confirm the view shows what you intend
Performance
Optimize Large Datasets
For datasets with 100K+ rows:- Filter early - Reduce row count before other operations
- Limit columns - Remove unnecessary columns
- Use pagination - Don’t load everything at once
- Export in batches - For very large exports
Import Efficiently
- Use CSV for large files (faster than Excel)
- Split very large files into chunks
- Remove unnecessary columns before import
Version Control
Leverage Version History
Rowbase automatically versions your data:- Before major changes - Note the current version
- After mistakes - Rollback to a previous version
- For audits - Export data from specific points in time
Create Checkpoints
Before significant transformations:- Export a backup
- Note the version number
- Document what you’re about to change
Security
Protect Sensitive Data
- Never include passwords or API keys in datasets
- Be cautious with PII (names, emails, addresses)
- Use view-only sharing for sensitive reports
- Audit who has access to sensitive projects
Manage Access Regularly
- Remove access when team members leave
- Review sharing settings quarterly
- Use project-level permissions over dataset-level when possible