Update now supports Scala, machine learning engines for visual data transformation, and an improved UX.
Dataiku, a analytics software company, has announced an update to its all-in-one predictive analytics platform Dataiku Data Science Studio (DSS). The 3.1 update now includes support for Scala for Apache Spark users, and features five new machine learning engines for visual data transformation.
The five new machine learning engines, HPE Vertica machine learning, H2O Sparkling Water, MLlib, Scikit-Learn, and XGBoo, enable users to create predictive apps within a code-free user interface. They’re available in the visual analysis section of DSS 3.1.
“With Dataiku DSS 3.1, we continue to bridge the gap between day-to-day analytic needs and the latest cutting-edge data science technologies,” said Florian Douetteau, CEO and co-founder of Dataiku, in the company’s announcement, “By adding additional machine learning engines and enabling development in Scala, we are bringing even more tools to the table. This allows our users to build the best and most dynamic data science applications – quickly.”
According to the announcement, additional new features include external databases offering integration with IBM Netezza, Google Big Query, SAP HANA and Tableau. There’s also an improved UX offering better navigation and all around improved user experience.
Dataiku’s DSS platform already supports languages and platforms including Python, R, SQL, Impala, Pig and Hive, the company stated.
