How to validate data, analytics, and data visualizations

February 28, 2019


Testing applications is a maturing discipline with tools that help quality assurance teams develop and automate functional tests, run load and performance tests, perform static code analysis, wrap APIs with unit tests, and validate applications against known security issues. Teams practicing devops can implement continuous testing by including all or a subset of their automated tests in their CI/CD pipelines and use the results to determine whether a build should be delivered to the target environment.

But all these testing capabilities can easily ignore one crucial set of tests that is critical for any application processing or presenting data, analytics, or data visualizations.

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