Data Science Studio 'Shiso' Release and Community Edition

Technology|Corporate| July 21, 2014| Clement

We are very proud to announce today the release of Data Science Studio V 1.2, codenamed Shiso. With this release, we now offer a free version: Data Science Studio Community Edition !

Less than two months after the release of the 'Yuzu' version, Data Science Studio 1.2 'Shiso' introduces new features that keep making Data Science more accessible to everyone with our Data Science Studio.

Let's have a look at what's new in this Shiso version!

Community Edition

Dataiku now provides a free edition of Data Science Studio: the Community Edition. It is a great way for a Data Scientist or any person interested in Data Science to get started with our sofware. You can download and install it on a Linux server. We support Ubuntu, Debian, CentOS, RHEL and Amazon Linux.

You may also sign up for a free online trial to get a hosted instance of the full edition of Data Science Studio.


Our advanced users need tools to run in production their best predictives models. Data Science Studio now allows you to schedule jobs every day or every hour directly within the UI (no command line anymore !).

It leverages our incremental build support, in order to just recompute and rebuild predictions on new data or data that has changed.

Cassandra and Impala Support

We keep on adding new integrations to our platform to let you work more efficiently with all the major Big Data technologies.

In Data Science Studio V1.2, we are happy to announce support for Cassandra (read and write) and Impala (queries and charts).


We recently introduced Pinboards that let you share charts and others insights (web applications, IPython notebooks, datasets, ...) with your collaborators and present them on a global dashboard.

Beta H2O support

Some Machine Learning algorithms can take quite a long time to run. Data Science Studio now features integration with H2O, a distributed machine learning framework.

This integration brings distributed implementations of a selected set of machine learning algorithms (Random Forest, Deep Learning, Gradient Boosting Methods).

Which better fits your data? scikit-learn or H2O? Find out with DSS.

This is just a highlight of the main features in Data Science Studio 1.2 'Shiso'. For more details, you can read our Release notes

We are eagerly looking for learning more about your great data science projects with Data Science Studio and waiting for your feedbacks!

Clement, CTO of Dataiku.

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