Data is dynamic. New data is continuously being captured, and older data may be updated to correct bad data points, fill in missing values, or substitute context-sensitive default values. Both scientific and commercial applications may need to re-analyze data, to reproduce results, compare results, validate results, and support audits.
SciDB contains capabilities for versioning your data and for distinguishing among many interpretations of missing values.
|Data is never overwritten, even when it is updated. SciDB versions data so you can re-analyze previous moment-in-time datasets.|
|SciDB query languages let you refer to specific array versions within queries, allowing you to reproduce previous results at any time.|
Missing Data Reason Codes
|SciDB supports multiple, custom-defined null values (such as data missing, source unavailable, trading halted, or instrument error) so that applications can substitute context-sensitive values.|
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About Paradigm4Paradigm4 is the company behind the open source SciDB project. We develop it, support it, build enterprise extensions, and provide hands-on expertise.