Dataiku's new AI tools reduce dependency on data science teams

Dataiku today expanded its effort to make AI accessible to the average business user with an update that makes it possible to run what-if simulations of AI models to determine how changes to the data they are based on will impact them. The goal is to make it easier for business analysts to experiment with AI models based on machine learning algorithms they can create with the help of a data scientist team, Dataiku CEO Florian Douetteau said. As part of that effort, Dataiku 9 adds a Model Assertions tool that enables a subject matter expert to inject a known condition or sanity-checks into a model to prevent a certain outcome or conclusion from ever being reached. There is also now a Visual ML Diagnostics tool that will generate error messages if the platform determines a model will fail and a Model Fairness Report tool that provides access to a dashboard through which companies can assess the bias or fairness of an AI model. Finally, there is also now a Smart Pattern Builder and Fuzzy Joins capability that makes it easier to work with more complex or even incomplete datasets without having to write code or manually clean or prep data.