Clean up messy data without writing code.

Every messy export looks the same. Inconsistent casing, blank cells, three different date formats, a duplicate row or two, and a column that's almost usable if you could just trim the whitespace. You open it in Excel, start hand-fixing, and an hour later you're writing a throwaway script you'll never reuse.

Data Wizard is the tool for exactly that job. Upload the file, clean and reshape it through a guided flow, and export the result — no formulas, no scripts, and nothing leaves your browser.

Three steps, no code

The whole thing is a wizard: Upload your CSV, Transform it, then Export. A progress bar keeps you oriented, and you can jump back a step whenever you need to. There's nothing to install and no query language to learn — if you can use a spreadsheet, you can use this.

What “transform” covers

Filter rows down to what you care about. Sort and aggregate to summarize. Join tables across multiple files as if they were one dataset. And the cleanup that eats your afternoon: trimming whitespace, standardizing dates to a single format, filling blank cells, and removing duplicate rows. You see the before-and-after as you go, so you always know what changed.

Your data never leaves your browser

All processing happens locally, in the browser tab. Your file isn't uploaded to a server, which matters when the data is a client's export, a list of customers, or anything you'd rather not hand to a third party. Close the tab and it's gone.

Export to anything

When the data's clean, export it as CSV, Excel (.xlsx), or JSON — ready to import somewhere, hand off, or drop into the next tool.

Data Wizard vs. Data Chat

Data Chatis for when you have a question and want to ask it in plain English. Data Wizard is for when the file itself is the problem — it's messy, and you need it clean and reshaped before it's any use to anyone. Both read the same files and both run in your browser, so you can clean a file in Data Wizard and then go ask questions of it in Data Chat.

Real scenarios

An ops person gets a CRM export with inconsistent company names and blank regions. They upload it, standardize the names, fill the blanks, drop the duplicates, and export a clean CSV ready to re-import — in five minutes, no data team involved.

A consultant lands on a client engagement with nothing but a browser. The client hands over a CSV, the consultant joins it against a reference file, filters to the relevant accounts, and exports the result — on their own laptop, no install, nothing leaving the client's environment.

What this isn't

It's not a data warehouse and it's not a dashboard that refreshes every morning. It's not built for pipelines shared across a 20-person team. It's for the everyday job of taking one messy file and turning it into a clean one — file in, file out.