Data validation
SigTech has a curated verification system that allows our engineers to ensure data quality.
Our data cleansing process is broken down into two steps:
- 1.Validation: an iterative process where we select checks to apply to datasets and resolve any errors that arise.
- 2.Cleaning: corrections and deletions are loaded in. The data is then stored to a separate storage facility.
Errors that surface following validation:
Icon | Status | Description |
|---|---|---|
 | Accepted | Accepted with individual errors. |
 | Amended / corrected | On the basis of an error, the data has been corrected. Example: an anomaly. |
 | Deleted | Data that shouldn’t be included. Example: an accidental entry. |
Tip: a fully validated timeseries or instrument is marked with a .
Note: default is clean data, but you have the option to select raw data.
Last modified 1yr ago