AI Data Quality Checker
Intelligently detect missing values, outliers, duplicates, format errors in datasets, generate quality reports and fix suggestions
Checker Interface
Interactive checker will be available soon
Features
- ✓ Automatically detect missing values, nulls, NULL distribution
- ✓ Intelligently identify outliers and anomalous points
- ✓ Detect duplicate data and near-duplicate records
- ✓ Validate data format, type, range constraints
- ✓ Generate visual quality reports and fix suggestions
How to Use
- Upload CSV, Excel or JSON data files
- Select check rules (missing values, outliers, duplicates)
- Configure threshold and tolerance parameters
- Click check, view quality report and fix suggestions
FAQ
How large data files are supported?
Supports files up to 100MB or 1 million rows. For larger datasets, API interface or batch processing is recommended.
How are outliers identified?
Uses multiple statistical methods: Z-score, IQR quartile range, Isolation Forest and other algorithms to automatically detect data points deviating from normal range.
Can I customize check rules?
Yes. Supports custom data types, range constraints, regex validation, business rules to meet specific scenario requirements.
What does the check report include?
Includes data overview, problem statistics, detailed problem list, visual charts, fix suggestions, data quality score and other complete information.
Does it support automatic data problem fixing?
Yes. Provides multiple fix solutions: fill missing values, delete outliers, merge duplicate records, format standardization, etc., can be applied with one click.