Greetings, RapidMiners around the world!
Once again, we’re excited to announce a series of updates to the RapidMiner portfolio. The latest innovations empower data scientists and business analysts in their quest to gain deeper and more directly actionable insight from Big Data.
With the latest innovations to the RapidMiner Modern Analytics platform include support for Apache Sentry enabling organizations to implement data authorization as part of their analytic initiatives in Hadoop. As Data Science is a team sport, RapidMiner raised the bar on their collaboration by adding workflow annotations to enhance analytic processes and overall outcomes. The latest platform updates enable users to efficiently develop RapidMiner extensions—add on packages contributed by the vast and extremely knowledgeable RapidMiner community—and leverage scripting languages more easily through new Python and improved R integrations.
The number one Big Data problem that is top of mind for the C-Suite is how to secure data, while gaining insight. With our latest enterprise-grade solution, RapidMiner provides peace of mind and further secures data as it is being mined for predictive insights. With RapidMiner, users are able to fully extract value from Big Data by identifying patterns and predicting more actionable outcomes. Through guided analytics, RapidMiner enables its users to build predictive analytics, accelerating time-to-insight, based on the wisdom gleaned from the 250,000-member RapidMiner community. Collaboration is central to everything we do at RapidMiner. We believe that the crowds have wisdom—that should be shared, whether to the broader community or within enterprises.
Key updates include:
The latest version of RapidMiner Radoop includes support for Apache Sentry. This enables users to control access to subsets of data based on management or functional roles. Sentry is the de facto standard for implementing data authorization and enables users to control access to data on a column and row level.
Apache Spark Machine Learning Library
RapidMiner Radoop features a new linear regression algorithm for Hadoop based on MLlib, the machine learning library of Apache Spark. As with all models being trained on Hadoop in a distributed fashion, the resulting linear regression model can be seamlessly used throughout the RapidMiner platform to be scored; in-memory on RapidMiner Server, in-Hadoop using RapidMiner Radoop or in-stream employing RapidMiner Streams.
RapidMiner now features a connector to Splunk, a well-adopted platform to search, monitor and analyze machine-generated data. With the connector, the data can be directly ingested into RapidMiner Studio for deeper analysis.
RapidMiner makes it easier to collaborate by offering the ability to annotate workflows with visual notes in RapidMiner Studio. This notes feature enables users to comment on a process as a whole, a part of a process or even individual steps within the process.
The RapidMiner Marketplace features a tighter integration with RapidMiner Studio allowing extensions to be downloaded and installed in RapidMiner Studio with just one click.
New Python and Enhanced R Integrations
Arbitrary scripts can be executed with R and Python directly in RapidMiner Studio, enabling data scientists and business analysts to seamlessly integrate R and Python for data transformations, model building and applications.
With nearly a third of all RapidMiner users working on Macs, RapidMiner has released a separate program to easily accelerate installation of RapidMiner Studio.
Extension Development Kit
With the new extension development kit, the process to build extensions is easier from start to finish. The kit includes a template that community members use to jumpstart the development process. (available within 30 days.)
At RapidMiner, we have a long history of listening closely to our 250,000+ users and giving them what they want. I’m proud of our engineering and product teams around the world for their hard work and commitment to our growing community.
I look forward to your comments and feedback about this exciting announcement.