A no-code data workbench for consultants and strategy professionals.
Built because of a real problem: moving from a large conglomerate with a dedicated analytics team into consulting, where you're often the only person who needs to wrangle data — with no SQL access, no Alteryx licence, and one consultant on the team.
DataBridge is a single HTML file that runs entirely in your browser. No installation. No Python. No server. No cost. Load a CSV or Excel file, apply operations from the panel, and export a clean result.
It covers the 20–25% of data operations that account for 90% of what consultants actually do on pricing, GTM, customer analytics, and finance projects.
Option A — Use online (no setup) Click the link above. Everything runs in your browser.
Option B — Use offline
Download databridge.html → double-click → opens in any browser. Works with no internet connection.
Loading data
- Click "Load dataset" or drag and drop files anywhere on the page
- Supports: CSV, TSV, Excel (.xlsx, .xls)
- Large files work fine — tested on 500K+ row transaction datasets
| Operation | What it does |
|---|---|
| Join tables | Inner, left, right, full outer join on a key column |
| Anti-join | Find rows in this table with no match in another |
| Union / Append | Stack two tables vertically |
| Lookup / VLOOKUP | Bring a single column from another table by key |
| Operation | What it does |
|---|---|
| Filter rows | Keep rows matching conditions — AND/OR logic, IN lists, .contains() |
| Select / drop columns | Choose which columns to keep or remove |
| Deduplicate | Remove duplicates — keep first, last, or flag all |
| Top / Bottom N | Get top or bottom N rows, overall or per group |
| Random sample | Sample by % or fixed count, with reproducible seed |
| Operation | What it does |
|---|---|
| Group by & summarise | Sum, count, count distinct, avg, min, max, median |
| Pivot | Turn row values into columns |
| Unpivot / Melt | Turn columns into rows |
| Running total | Cumulative sum within a group |
| Percent of total | Each row as % of group or grand total |
| Operation | What it does |
|---|---|
| Calculated column | Add a column with arithmetic, IF/THEN/ELSE, or CASE WHEN |
| Date parts | Extract year, quarter, month, week, day, weekday |
| Date difference | Days, months, or years between two date columns |
| Text operations | Trim, upper/lower, concat, split, left/right/mid, extract numbers |
| Find & replace | Replace values — plain text or regex |
| Bin / bucket | Turn continuous numbers into range buckets |
| Rank | Rank, dense rank, or row number within a group |
| Lag / Lead | Previous or next row value within a group |
| Fill nulls | Replace missing values with constant, mean, median, forward/backward fill |
| Rename columns | Rename one or more columns |
| Change data type | Cast to number, text, or date |
| Operation | What it does |
|---|---|
| Column summary | Min, max, mean, median, distinct count, % null for every column |
| Null audit | Count and % of missing values per column |
| Duplicate finder | Show which rows are duplicates |
| Value frequencies | Top N most common values in a column |
| Crosstab | Two-way frequency table between two columns |
| Correlation matrix | Pairwise correlation for numeric columns |
| Pareto / 80-20 | Cumulative % of total, sorted descending |
| Operation | What it does |
|---|---|
| Conditional tagging | Assign segment labels based on IF/THEN rules |
| Percentile / decile | Assign quartile, decile, or custom percentile buckets |
| Flag first / last | Flag first or last occurrence per group |
| Operation | What it does |
|---|---|
| Period comparison | Add prior-period value column — YoY, MoM, WoW, QoQ |
| Rolling average | Trailing N-period average, sum, min, or max |
| Fiscal calendar | Map dates to a fiscal year starting any month |
DataBridge uses a natural language formula syntax — no SQL required.
[Revenue] / [Units] → arithmetic
[Price] * (1 - [Discount]) → calculated column
IF [Status] == 'Won' THEN 1 ELSE 0 → conditional
CASE WHEN [Score] > 80 THEN 'High'
WHEN [Score] > 50 THEN 'Mid'
ELSE 'Low' → multi-condition
Filter expressions:
[Revenue] > 10000
[Region] == 'North' AND [Status] != 'Closed'
[Category] IN ['A', 'B', 'C']
[Name].contains('Smith')
[Date] > '2023-01-01' AND [Date] <= '2023-12-31'
- Pipeline bar — every step you've applied is visible at the top. Remove any step to rewind.
- Undo — step back one operation at a time
- Audit log — every operation logged with input/output row counts. Click "Audit log" top right.
- Preview with sort & search — click any column header to sort; search box filters all columns
- Export — CSV or Excel (.xlsx). "Copy to clipboard" for pasting directly into slides.
- Large file support — renders 500 rows at a time, loads more on demand
The target user is a strategy consultant or analyst who:
- Doesn't have Python or a terminal workflow
- Works on client machines where they can't install software
- Needs to share the tool with a colleague instantly ("just open this file")
- Works offline in client offices or on flights
A single .html file satisfies all of these. It runs on Windows, Mac, Linux, or any tablet. No dependencies. No login. No data ever leaves the browser.
DataBridge uses JavaScript's native array operations. Tested on:
- 500K rows × 15 columns — loads in ~3 seconds, operations in <1 second
- 1M+ rows — loads in ~8 seconds, simple operations in 1–3 seconds
- For very large files, operations like correlation and crosstab may take a few seconds
For datasets above 2M rows, consider filtering down first or using a dedicated SQL tool.
- Complex nested subqueries — the visual pipeline handles this implicitly by chaining steps
- Database connections — by design (works offline, no credentials)
- Machine learning / statistical modelling — use Python/R for that 5%
- Stored procedures, loops, variables
Archishman Bandyopadhyay — strategy consultant, 12 years across Accenture, Monitor Deloitte, Mahindra, Tata Motors.
Built because I needed it. On my first pricing analytics engagement at Deloitte — working with a single consultant and no Alteryx licence — I spent too much time in Excel doing things that should have taken seconds. This is the tool I wish I'd had.
Part of a 50-week public build — translating consulting experience into open-source tools.
Issues and PRs welcome. The most useful contributions are:
- Additional formula functions
- Reported edge cases on unusual CSV formats
- UI improvements for the operation modals
MIT — use freely, in client engagements or otherwise.