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CSV upload is Summand’s no-setup entry point. It’s available on every tier, including Free.

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Limits

For files larger than 4 GB, point Summand at the source via a database connector or Fivetran instead — uploads aren’t the right tool for very large data.

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File format

1

UTF-8 encoded text

Other encodings (UTF-16, ISO-8859-1, Windows-1252) often work but aren’t guaranteed. If column names look garbled in the preview, re-export as UTF-8.
2

One header row

The first non-empty row must contain column names. Names should be unique and human-readable; Summand uses them in the UI verbatim.
3

Comma delimited, with a .csv extension

Only .csv files are accepted, and fields must be separated by commas. Convert tab- or semicolon-delimited files to comma-delimited CSV before uploading.
4

Long format, not wide

One row per observation, one column per variable. Pivot tables and crosstabs produce noisy analyses — un-pivot first.

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What happens when you upload

  1. The file streams directly to Summand’s encrypted S3 bucket via a presigned URL — it doesn’t pass through any application server.
  2. Summand reads a sample from the start of the file to infer column types, and creates the dataset.
  3. The full file is converted to an Iceberg table (Parquet files) in Summand’s storage, and column statistics are computed. The dataset is then ready to query.
  4. Analysis components, such as those that produce a computed-context version, run when you ask for them in chat or set up an experiment.
For a 100 MB file, end-to-end is typically under a minute.

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Re-uploading

To analyze a new version of the same file, use Upload a new version on the dataset page. The upload writes a new snapshot of the same dataset. Earlier snapshots stay queryable for at least 30 days by default. The dataset’s context, sharing grants, and any experiments configured on it are preserved across re-uploads, so you don’t redo configuration.

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Troubleshooting

Large files upload in parts. If an upload fails, start it again. If it still fails, the file may be corrupted. Open it in a text editor or spreadsheet to confirm it’s well-formed.
Most often this is non-numeric content in the column — currency symbols, units, commas as thousands separators. Either clean the file and upload a new version, or cast the column in a view.
Three common causes: (1) the target is highly imbalanced — fewer than ~30 minority-class rows; (2) too many features are high-cardinality strings excluded from the model; (3) the file is too small — EBM needs roughly 500+ rows for stable shape functions.