The latest version of Data Science Studio came out last week and we were super excited at Dataiku about the integration of Spark! But DSS 2.1 has so much cool new stuff in it, I just had to tell you about all of our new features!
Honestly we were being modest when we made this version a minor release. Some would even say, the release of DSS 2.1 is as big of a deal as the Apple Keynote. It has so many new features that make it a great tool to use everyday. But you shouldn't take my word for it, let me show you, the Apple way.
Let’s start with the simplest DSS 2.1 innovation: the new and improved Charts module.
We’ve redesigned the whole visual interface to make it easier to get the visualization of your data you really want. And it’s not just prettier, we’ve also added lots of new charts so you can find the right one to explore your data. There are now really too many for me to enumerate here so go check it out.
DSS makes writing code in the notebooks so much easier with code samples. As you use the notebook, add your own favorite code snippets with the bits you find that you’re rewriting all the time! We’ve added a bunch in the Studio so now you can start right away with pre-written common functions.
And because DSS was built as a collaborative tool first and foremost, you can share these with all your DSS-friends. The learning curve in the Studio just got that much steeper. (Yes that makes sense, your learn faster)
Create your own folders of filesystem-hosted datasets, where you can store any kind of data and read and write to and from them with DSS code recipes.
You can also transform your datasets into editable datasets and add notes about your data. Or create editable datasets from scratch. Did i I hear uhm why?
Well for those times you want to add information to your data without having to change your dataset, write comments about a client contact or a transaction or create a reference table to enrich a dataset with specific information, you can create an editable dataset, from an existing dataset or from scratch, like you would for an excel file or a Google Spreadsheet.
Data Science Studio 2.1 takes it one step further to bring data from absolutely all of your data sources in the Studio, seamlessly, with plugins. Check out Dataiku’s certified plugins or our community developped connectors to connect to all your data sources, adding custom code snippets or sample projects, and plugins to enrich your data with APIs and push it to anywhere you really need it. All this through our visual interface. That’s right, no code.
Anyone can develop their own plugins easily from their own code and add them to our community platform. So your team and your whole company can profit from your projects. Bragging rights are all yours.
Our public API is also there to help developers get real-life business uses from projects in the Studio.
Shell recipes are the final step to a complete collaborative experience. They make it possible for your data infrastructure developers to use their languages in the Studio and to collaborate with data scientists and analysts in real time.
Spark speed for data preparation in the visual interface, SQL, R, and Python recipes, distributed Machine Learning and training and prediction in your Flow.
Enjoy the next big thing. The future is here. Start writing YOUR data story now.
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