Holistic data application quality – Lars Albertsson, Scling

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Session Outline

The quality of data-powered applications depends not only on code, but also on collected data, as well as models trained on data. This renders traditional quality assurance inadequate. We will take a look in our toolbox for more holistic tactics that bridge the gap between code and data quality assurance.

Key Takeaways

  • Why traditional quality assurance is insufficient for data-powered applications.
  • Tactics for adapting software testing techniques to include data testing.
  • Combining testing and monitoring to achieve holistic application quality.

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