RapidMiner today announces a cloud-based version of its predictive analytics platform that brings the benefits of cloud computing to its renowned machine learning and analytics technology. The generally available RapidMiner Cloud provides customers with an elastic computing platform, the capability to combine disparate data sources and a cloud repository that allows analysts to connect to the RapidMiner cloud and run analytics from a web-enabled machine. RapidMiner Cloud users can take advantage of the company’s preconfigured library of best practices for running analytics via a graphical user interface that absolves analysts of the need to write code as illustrated by the screenshot below:
Analysts can select different datasets and perform analytic operations without writing code by creating analytic workflows as shown in the graphic above. In addition to predictive analytics, RapidMiner Cloud provides support for data integration, data cleansing, data deduplication and data enrichment. As told to Cloud Computing Today in a phone interview with Ingo Mierswa, CEO of RapidMiner, the platform’s predictive analytic technology facilitates data enrichment by allowing analysts to use predictive algorithms to estimate values for missing or corrupt data. Moreover, RapidMiner Cloud integrates with over 300 cloud platforms including Amazon, Salesforce.com, Twitter and Dropbox. RapidMiner’s integration with Amazon S3, for example, means that data stored within S3 can be accessed by RapidMiner via a connector, and analyzed without the raw data being imported directly into the RapidMiner cloud platform. The platform’s ability to integrate with other vendors underscores the increasing importance of APIs and connector infrastructure components in a world in which organizations increasingly confront the challenge of data sharing across different platforms given the ubiquity of cloud-based data.