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Framework v8
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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.
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.
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Position rounding
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