Inspect data quality
Review missingness, uniqueness, inferred types and numeric summaries.
Try Data Quality Profiler →CHOOSE THE RIGHT TOOL
Data
Turn raw records into reliable, useful data. Inspect, clean, reshape and analyze without creating a workbook.
SQL Data Explorer
Parquet Viewer & Converter
SQLite Database Explorer
SQL Dump Extractor
XML Data Extractor
HTML Table Extractor
JSON Schema Validator
Chart-to-Data Digitizer
Survey Results Analyzer
Time-Series Resampler
Rolling Metrics & Growth Analyzer
Time-Series Forecast Studio
Event Session Analyzer
Event Funnel Analyzer
User Journey Explorer
RFM Customer Segmentation
Market Basket Analyzer
Customer Lifetime Value Analyzer
Revenue Concentration & Pareto Analyzer
Subscription Churn & Revenue Retention
Dataset Drift Detector
Dataset Schema Change Checker
Data Dictionary Builder
Group Comparison Analyzer
Regression & Residual Analyzer
Numeric Scaling & Normalization
Categorical Data Encoder
Class Balance & Resampling
Coordinate Format Converter
GPX/KML Track Analyzer
Data Quality Profiler
Missing Value Cleaner
Outlier Detector
Data Validation Rules
Group & Aggregate Data
Pivot & Unpivot Data
Data Filter Builder
Column Split & Extract
Data Value Mapper
Fuzzy Record Matcher
Dataset Sampler & Splitter
Data Anonymizer
Value Cluster Cleaner
Date Column Normalizer
Number Format Normalizer
JSON Schema Inference
GeoJSON Inspector
Log Data Analyzer
A/B Test Analyzer
Cohort Retention Analyzer
CSV Editor
CSV Merger & Joiner
CSV Splitter
CSV Duplicate Remover
CSV Compare
Excel to CSV
CSV to Excel
PDF to Excel
Text to Table
JSON to CSV Converter
Which tool should I use?
Clean missing values
Use explicit fill rules and review every changed value.
Try Missing Value Cleaner →Validate records
Separate passing records, failing records and rule findings.
Try Data Validation Rules →Find approximate matches
Review ranked string candidates without automatic merging.
Try Fuzzy Record Matcher →Protect identifiers
Create consistent pseudonyms or redact selected columns locally.
Try Data Anonymizer →Understand retention
Inspect first-observed cohorts and complete calendar periods.
Try Cohort Retention Analyzer →Reshape existing records
Pivot or unpivot actual values with explicit identifiers.
Try Pivot & Unpivot Data →Inspect existing CSV files
Keep the established CSV editor, joins and comparison utilities.
Try CSV Editor →Explore a related workflow
- SQL Data Explorer: methods and data limits
Query local records with joins, CTEs and window functions.
- Parquet Viewer & Converter: methods and data limits
Inspect local Parquet metadata and export selected records.
- SQLite Database Explorer: methods and data limits
Explore tables, indexes and foreign keys in a local database.
- SQL Dump Extractor: methods and data limits
Extract literal INSERT records without executing backup SQL.