Overview
Rowbase provides powerful tools to understand your data quality, make corrections, and ensure data meets your standards before use.Diff View
Compare source data to transformed output
Inline Editing
Edit cells directly with automatic correction tracking
Data Profiling
Get instant statistics for every column
Quarantine
Isolate problematic rows for review
Diff View
Compare your source data to the transformed output to see exactly what changed.Using Diff View
- Open a dataset with operations applied
- Click the Diff button
- View row-by-row changes
What Diff Shows
| Status | Description |
|---|---|
| Added | New rows created by operations |
| Removed | Rows filtered out or quarantined |
| Modified | Rows with changed values |
| Unchanged | Rows that passed through unchanged |
- Which columns were affected
- Before and after values for each change
- Summary statistics (total added, removed, modified)
Data Profiling
Get instant statistics and distributions for every column.Profile Information
For each column, the profile shows:- Type - Detected data type (text, number, date, boolean)
- Unique values - Count and percentage
- Null values - Count and percentage
- Top values - Most frequent values with counts
- Min, max, mean, median
- Standard deviation
- Histogram distribution
- Length statistics
- Character pattern analysis
- Common prefixes/suffixes
Viewing the Profile
- Open a dataset
- Click the Profile tab
- Explore statistics for each column
Inline Cell Editing & Corrections
Edit any cell directly in the data grid. Your changes are tracked as corrections.How Corrections Work
Corrections are stored separately from your data and operations. They’re applied last, after all operations run, so:- Original data is never modified
- Corrections persist across new data versions
- You can see and manage all corrections
Making a Correction
- Click on a cell
- Edit the value
- The correction is saved automatically
Viewing Corrections
Corrected cells show a visual indicator. You can:- View all corrections in the Corrections panel
- See who made each correction and when
- Revert individual corrections
Corrections are applied via the Apply Corrections operation in your pipeline. This operation is added automatically when you make your first correction.
Quarantine
Isolate problematic rows for review without deleting them.Automatic Quarantine
Use the Quarantine If operation to automatically quarantine rows that fail validation:Manual Quarantine
You can also manually quarantine rows:- Select rows in the data view
- Click Quarantine
- Add a reason (optional)
Working with Quarantined Rows
Quarantined rows are:- Excluded from the main data view
- Stored in a separate quarantine table
- Available for review and restoration
- Open the Quarantine panel
- Review the row and reason
- Click Restore to bring it back
Validation Operations
Build validation rules into your pipeline:| Operation | Purpose |
|---|---|
| Require Fields | Ensure columns are not null |
| Unique Constraint | Ensure values are unique |
| Primary Key | Combine uniqueness + not-null |
| Validate Schema | Check types match expectations |
| Quarantine If | Quarantine rows failing a formula |
Quality Flags
Flag rows with potential issues without quarantining them:- Flag Negative - Negative numeric values
- Flag Zero - Zero values
- Flag If Less Than - Column A < Column B
- Flag Invalid Units - Units not in allowed list
Best Practices
Profile before transforming
Profile before transforming
Run the profiler first to understand your data. This helps you choose the right operations.
Use quarantine over delete
Use quarantine over delete
When in doubt, quarantine problematic rows instead of deleting. You can always restore them later.
Check the diff
Check the diff
After applying operations, use diff view to verify the changes match your expectations.
Build validation into pipelines
Build validation into pipelines
Add validation operations so future data imports are automatically checked against your rules.