201 tools across 19 categories. Search by name, filter by category, or jump straight to a sub-section below.
Drop in a file, profile it, clean it, visualize it — all in one workspace.
Drop in any CSV/JSON/Excel/XML — auto-detect, profile, clean, visualize, export.
Open any JSON, browse, search, edit, and export — all in one workspace.
Open any CSV, profile columns, filter rows, edit cells, export.
Open multi-sheet Excel, profile columns, inspect formulas.
Convert between JSON, CSV, YAML, XML, SQL and more.
Convert a JSON array of objects into clean CSV.
Parse CSV into JSON — with header detection.
Convert between JSON and YAML in either direction.
Convert XML documents to JSON.
Convert JSON to XML.
Convert .xlsx sheets into CSV.
Generate a downloadable .xlsx from CSV.
Switch tab-separated to comma-separated.
Generate INSERT statements from CSV rows.
Turn a CREATE TABLE schema into JSON.
Generate SQL DDL from sample JSON.
Infer a JSON Schema from sample data.
Generate TS interfaces from JSON.
Generate Java POJO classes from JSON.
Generate Python @dataclass code from JSON.
Generate a Prisma schema from a sample.
Generate a Mongoose schema from JSON.
Deep-merge two or more JSON documents with conflict policy.
Split a large JSON array into N chunks or by predicate.
Test JSONPath / jq-style expressions against a JSON document live.
Search keys and values across deeply nested JSON.
Flatten nested JSON to dot-notation keys, or unflatten back.
Pull a specific nested branch out of a large JSON document.
Generate a downloadable .xlsx from JSON data.
Generate a Mongoose schema from a sample JSON document.
Convert tabular CSV into XML rows.
Read .xlsx and emit JSON per sheet.
Run a query result mock and emit JSON.
Generate a Prisma schema from CREATE TABLE statements.
Translate MySQL DDL/DML to PostgreSQL dialect.
Deduplicate, normalize, repair, and standardize data.
Strip duplicate rows from CSV or JSON.
Drop empty cells or null fields.
Trim leading/trailing whitespace in every field.
Repair trailing commas, single quotes, comments.
Auto-detect and fix common CSV issues.
snake_case, camelCase, or kebab-case headers.
Convert phone numbers to a single format.
Bulk-validate a list of email addresses.
Infer each column's data type.
Spot rows with shape or type mismatches.
Report empty/null cells per column.
Flag inconsistent formats inside a column.
Replace, drop, or report null/empty cells.
Flag statistical outliers in numeric columns.
Rename keys with rules (snake_case, prefix strip, mapping table).
Detect, drop, fill, or interpolate missing values per column.
Per-column type inference: int, float, date, bool, enum, ID.
Flag rows that violate a schema or per-column constraints.
Normalize a column to a chosen format (e.g. dates, currencies, casing).
Reformat phone numbers (E.164, national, dashed) in a CSV column.
Parse messy date strings and emit ISO-8601 (or any chosen format).
Normalize currency strings ("$1,200.50" → 1200.50 USD) across rows.
Standardize address strings — case, abbreviations, components.
Beautify, minify, and re-indent your data files.
Pretty-print, minify, and indent JSON safely.
Pretty-print XML with proper indentation.
Reformat SQL queries with proper line breaks.
Tidy YAML structure and indentation.
Align CSV columns visually.
Format and explore deeply nested JSON.
Browse JSON/XML as a collapsible tree.
Normalize indentation across the file.
Switch between minified and pretty form.
Check syntax for JSON, XML, YAML, emails, URLs, more.
Validate JSON syntax with helpful error messages.
Check XML well-formedness.
Catch YAML syntax errors.
Catch ragged rows and quoting issues.
Lint SQL syntax across dialects.
Validate JSON against a JSON Schema.
Bulk URL syntax checker.
Validate phone numbers in bulk.
Validate IPv4 and IPv6 addresses.
Validate card number format and Luhn check.
Turn CSV/JSON/SQL into instant charts and dashboards.
Render quick charts from a CSV.
Render charts directly from JSON data.
Turn a spreadsheet into a small dashboard.
Visualize a SQL query result instantly.
Build a pie chart from any column.
Plot time series or sequences.
Show single-metric KPI cards.
Visualize a matrix as a heatmap.
Plot the distribution of a numeric column.
Visualize relationships between two columns.
Compose a small dashboard out of KPI cards + charts on a CSV.
Visualize flow between source/target columns.
Build a treemap from a hierarchical categorical column.
Plot one or more numeric columns over a date column.
Drag a column onto X / Y / color and a chart appears.
Live filters across all charts on a multi-chart canvas.
Edit data → dashboard updates instantly. Great for QA.
Summaries, statistics, distributions, correlations.
Count rows in a dataset.
Type, range, nulls for every column.
Count distinct values per column.
Percent of missing values per column.
Quantify exact and near-duplicates.
Central tendency for numeric columns.
Compute σ and variance per column.
Pairwise correlations between numeric columns.
Skewness, kurtosis, histogram per column.
Per-column types, ranges, uniques, nulls.
Surface duplicate rows by chosen key columns.
Min/max/mean/median/stddev/quartiles for every numeric column.
Histograms / KDE per column with quick outlier flags.
Value-count tables for categorical columns.
A heatmap that shows where the gaps are in your dataset.
Per-row z-scores for any numeric column with outlier highlights.
Quick linear / polynomial fit + R² for two columns.
Surface monotonic trends, level-shifts, and seasonality in time series.
Pipelines: extract, transform, load — without code.
Upload, transform, map, and export visually.
Bulk-rename CSV/JSON columns.
Concatenate or join two tabular files.
Filter rows by predicate.
Sort by one or more columns.
Recast columns: string ↔ number ↔ date.
Merge multiple CSV files into one — header-aware.
Build complex row filters across columns visually.
Drag-and-drop ETL canvas: upload, transform, map, merge, export.
Chain validators on a dataset and surface row-level failures.
Query helpers, seed data, fake datasets, joins.
Realistic seed data on demand.
Generate INSERT seed scripts.
Create fake user records (name, email, address).
Create fake product records.
Format ugly SQL into readable layouts.
Export a result set to CSV/JSON/Excel.
Build SELECT/JOIN queries with a form.
Diagram inner/outer/left/right joins live.
Token-based SQL formatter (dialect-aware).
Inspect a query: tables, joins, projections, filters.
Pretty-render an EXPLAIN plan as a tree.
Static heuristics: missing indexes, SELECT *, cartesian joins.
Generate an ER diagram from CREATE TABLE statements.
Visualize FK relationships across a schema.
Browse tables/columns of a SQL schema interactively.
Show which tables a CTE / view depends on.
Build SELECT/JOIN/WHERE/GROUP queries with a form.
Build INNER/LEFT/RIGHT/FULL joins visually with key picker.
Build GROUP BY / HAVING / window aggregations visually.
Excel sheet tools, splitters, pivots, formulas.
Open .xlsx files directly in the browser.
Split a column by delimiter into multiple.
Generate Excel/Sheets formulas from prose.
Highlight duplicate rows in a sheet.
Build complex filters across columns.
Build pivots without Excel.
Trace and explain Excel formulas.
Generate conditional-formatting rules.
Open every sheet of an .xlsx file and switch between them.
Per-column types, distributions, nulls for every sheet.
Rich pivot tables with row/col/value/agg pickers.
Format, analyze, and map JSON API responses.
Pretty-print and inspect API JSON.
Inspect shape, types, and nesting.
Infer a schema from sample responses.
Map fields between two API shapes.
Parse and analyze access and application logs.
Pretty-print structured logs.
Browse structured JSON logs by field.
Group errors and surface hot spots.
Parse Apache access logs into structured rows.
Summarize Nginx access logs.
Group log lines by signature; surface error spikes.
Plot log volume over time with a brushable timeline.
Lightweight viewers for huge CSV, JSON, NDJSON.
Split a huge CSV into manageable chunks.
Browse multi-MB JSON without freezing the tab.
Stream and browse newline-delimited JSON.
Convert many files in one go.
Render any JSON as an interactive collapsible tree.
Open and browse any CSV — sortable, filterable, searchable.
Split a large CSV into N files by row count, by value, or by hash.
Full-text search across every cell of a CSV.
Sample N rows / X% / stratified samples from large CSV.
Estimate browser memory cost of a dataset before loading it.
Stream a huge CSV in chunks and expose pause/resume controls.
Smart cleaning, schema detection, natural-language SQL.
One-click dataset cleaning suggestions.
Map fields between two datasets with AI.
Detect schema and types from any sample.
Generate SQL from a plain-English question.
Auto-surface notable findings in a dataset.
Scan a dataset and suggest fixes — types, nulls, formats.
Auto-map source columns to a target schema with confidence scores.
Auto-detect schemas, profile metadata, document datasets.
Infer a schema (types, nullability, uniqueness) from any sample dataset.
Generate a markdown / CSV data dictionary from any dataset.
Extract row count, column types, file size, byte distribution.
Spot foreign-key candidates and 1:1 / 1:N relationships.
Survey, SPSS, and thesis-grade data utilities.
Clean exports from common survey tools.
Reshape CSV for SPSS-friendly import.
Quick visualization for research data.
Summary, charts, and tests for thesis data.
Diff JSON, CSV, SQL results, and datasets.
Row-level diff between two CSV files.
Find missing or changed records.
Compare two query result sets.
Side-by-side diff of two JSON documents with structural alignment.
Pull emails, URLs, phones, keywords from text.
Pull every email address from any text.
Extract all URLs from text or HTML.
Find phone numbers in unstructured text.
Surface the most relevant keywords.
Pull tables, JSON-LD, and OpenGraph blocks out of HTML.
Mask sensitive fields, detect PII, scan datasets.
Mask sensitive fields in a dataset.
Replace real fields with realistic fakes.
Scan tables and text for likely PII.
Flag credit cards, SSNs, tokens, keys.
