Dotwave Upload your first dataset
Everything in Dotwave starts with a dataset. Before you can clean, chart, or share anything, you upload a file — and Dotwave is deliberately forgiving about what that file looks like. This article walks through the supported formats, the upload flow, and what happens automatically once your data lands.
Supported file formats
Dotwave reads the formats analysts actually receive from clients:
- CSV (.csv) — comma-separated or semicolon-separated. Dotwave detects the delimiter for you, which matters for European exports that use semicolons.
- TSV (.tsv) — tab-separated values, common in exports from databases and older tools.
- Excel (.xlsx and .xls) — both the modern and legacy Excel formats are supported.
The maximum upload size is 100MB per file. That comfortably covers most client exports; if your file is larger, consider splitting it or pre-filtering to the rows you actually need before uploading.
How to upload
From the home screen, select Add data source to begin.
Pick the CSV / Excel option to upload a file from your computer.
Click the upload area to browse, or drag the file directly onto it.
Give it a descriptive name — something like Acme Q3 sales is easier to find later than the raw file name.
Confirm the upload to send the file to Dotwave.
Dotwave parses and profiles the file, which usually takes under 10 seconds.
When the status shows Ready, click the dataset to open it.
What happens after upload
Uploading is not just storage — Dotwave immediately gets to work understanding your data. As soon as the file is parsed, it auto-profiles every column: it infers each column's type, counts the null values, detects duplicate rows, and flags data-quality issues it spots along the way. This profile is what powers the AI suggestions later, because the assistant reads the profile rather than your whole dataset.
The moment profiling finishes, the 4-step cleaning pipeline opens automatically, dropping you straight into Step 1 — Understand your data. You do not have to go looking for it. From there you can review what Dotwave found and start applying fixes.
Try a real client file — the messier the better. Dotwave is designed for real-world data, not spotless test files, so you will get far more value from a genuine export with missing values and inconsistent formatting than from a tidy sample.