Dataiku 11.3 Introduces Brand-New Features Including Visual Time Series Forecasting

Dataiku is releasing version 11.3 of its platform, delivering brand-new features for data analysts, data scientists, and ML engineers and operators.

Dataiku 11.3 highlights include:

  • The “Anti-Join” Dataset - In addition to producing the output dataset containing the records that meet the join conditions, the join recipe can now optionally output a dataset that returns the unmatched rows for further analysis.
  • Share and Export Filtered Views
  • Shortcut to Visual Previews for Images and Geospatial Data - In addition to the full-table image view released with Dataiku 11.2, you can now use the convenient “preview” action to preview individual images or geolocations.
  • Deep Neural Network as a Native Algorithm - Based on the multilayer perceptron (MLP) architecture, this Deep Neural Network leverages state-of-the-art libraries for a robust, efficient, and scalable model.
  • Feature-level View and Search in the Feature Store
  • Visual Time Series Forecasting: Evaluate Beyond Forecast Horizon - If you don’t plan to retrain the model as frequently as the forecast horizon, you can now specify an evaluation period longer than the horizon.
  • Evaluation-Ready Event Logs - With the Dataiku 11.3 update, the evaluate recipe is now able to automatically process those prediction logs. This removes the need for a preceding prepare recipe and simplifies the setup of production model monitoring.
  • Prediction Drift Detection Without Ground Truth - Take advantage of prediction drift analysis in Dataiku’s model evaluation store with just the prediction logs - even without ground truth labels.

For more information about these features, visit


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