Getting Started: Data Sources
Every synthetic dataset starts from a raw source dataset whose statistical structure you want to reproduce. The current workspace accepts that dataset as an Excel workbook and analyses it before generation begins.
Raw data upload
Upload your source dataset as an Excel file, and the module analyses it automatically.
Accepted files
| Property | Requirement |
|---|---|
| Format | Excel .xlsx or .xls |
| Maximum file size | 50 MB |
| Maximum rows | 100,000 |
| Recommended maximum columns | 200; larger files can proceed with a performance warning |
| Layout | One row per observation, one column per variable, with a header row |
The Upload Your Dataset panel accepts a file by drag-and-drop or by browsing. Once dropped, it is validated immediately.
File validation
Errors (block the upload):
| Condition | Message |
|---|---|
| File larger than 50 MB | "File size exceeds 50MB limit. For larger datasets, please contact us at info@epicosai.com for custom solutions." |
| Not a recognised format | "Invalid file format. Please upload an Excel file (.xlsx or .xls)." |
| File cannot be read | "Failed to read the Excel file. Please check the file format." |
Warnings (do not block, but flag a concern):
| Condition | Warning |
|---|---|
| More than 200 columns | "Dataset contains N columns. Maximum recommended is 200 columns. Processing may be slower with more columns." |
| Fewer than 2 columns | "Dataset has very few columns. Make sure your data is properly formatted." |
| Fewer than 10 rows | "Dataset has fewer than 10 rows. Results may not be statistically meaningful." |
| More than 50,000 rows | "Dataset contains N rows. Processing may take longer than usual." |
| Empty/blank column headers | "Some column headers are empty or contain only spaces." |
| Numeric column names | "Some columns have numeric names. Consider using descriptive text headers." |
After a successful upload, the module reports the dataset's dimensions and moves on to automatic analysis.
What happens after the source is loaded
After the workbook is loaded, the module produces an internal model:
- A list of variables, each with a detected type
- A distribution with parameters for each variable
- The relationships between variables (correlations and effect sizes)
You then review and adjust these in the Configure Settings step before generating.