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:
Validation: an iterative process where we select checks to apply to datasets and resolve any errors that arise.
Cleaning: corrections and deletions are loaded in. The data is then stored to a separate storage facility.
Errors that surface following validation:
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.