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:
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Status
Description
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Accepted
Accepted with individual errors.
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Amended / corrected
On the basis of an error, the data has been corrected. Example: an anomaly.
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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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