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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. 1.
    Validation: an iterative process where we select checks to apply to datasets and resolve any errors that arise.
  2. 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.
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