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Dataiku DSS 3.1 – Now with 5 ML Backends & Scala!


Introducing Dataiku DSS 3.1, with new visual machine learning engines that allow users to create incredibly powerful predictive applications within a code-free interface.



Dataiku DSS 3.1
Now with 5 ML Backends & Scala!

Dataiku DSS 3.1 introduces new visual machine learning engines that allow users to create incredibly powerful predictive applications within a code-free interface. Users of all skill levels can now leverage HPE Vertica machine learning, H2O Sparkling Water, MLlib, Scikit-Learn, and XGBoost directly from within the visual analysis section of Dataiku DSS 3.1 to apply powerful machine learning algorithms to their data science projects without having to write a line of code.

The blending of visual code-free and free-form code-based transformations is one of the main strengths of Dataiku DSS for the prototyping and production of data applications. In addition to Python, R, SQL, Hive, Impala, and Pig, Dataiku DSS 3.1 now enables Apache Spark users to write transformations and interactive notebooks in Scala, bringing the power of Spark's native and most performant language to data analysts using Dataiku DSS.

Additional features of Dataiku DSS 3.1 include:
  • New external databases: integration with IBM Netezza, Hana, and Big Query.
  • Improved UX: fluid navigation and project dependencies for optimized user experience and project management.
  • Seamless Integration with Tableau: users can extend Dataiku DSS compatibility by creating custom export formats for datasets, including Tableau .tde files. This allows for better integration with Tableau and other tools.

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