RapidAnalytics suite consists of RapidMiner predictive analytics and RapidReporting (BI reports and dashboard). Built on top of these are some solutions including RapidLab for configuration, RapidNet for network analysis and RapidSentilyzer to analyze web text for sentiment.
JTonEDM.com, James Taylor, March 27, 2012
provides open source software for predictive analytics, data mining and text mining. Incorporated in 2006, they are based in Dortmund Germany and have been working on RapidMiner since 2001. They have over 35,000 production deployments and more than 400 customers in 40 countries. Banking and financial services is their largest market followed by Pharma and, interestingly, manufacturing. Customers include some large companies such as Siemens, Pepsico and Allianz. Their RapidAnalytics suite consists of RapidMiner and RapidReporting which offers traditional business intelligence reports and dashboard in addition to predictive analytics. Built on top of these are some solutions including RapidLab that is designed to be prescriptive (for instance to help people configure a machine based on its predicted/simulated behavior), RapidNet for network analysis and RapidSentilyzer to analyze web text for sentiment.
is a classic data mining workbench that allows a set of nodes to be linked to create data mining processes. Rapid-I think of RapidMiner as a process execution engine for the processes involved in data mining and analytics and provide a workbench to manage these processes as well as a server, web-based interfaces and an API. RapidMiner can be extended and has large numbers of extensions built by third parties. Rapid-I themselves also extended, for instance to handle Hadoop with a product called
Key features of RapidMiner include:
- A GUI for analytics that handles more than 1,500 basic operations in the predictive analytic process with numerous extensions.
- Everything is considered a process so everything built in Rapid Miner can be extended and reused- there are no breaks between functions for ETL, data transformation and modeling for example.
- Supports in-database, streaming and Hadoop data
- Lots of automated analysis of problems and potential problems in the processes defined that are brought to the attention of the analyst
- Connectors for R, Weka and others
- A marketplace for extensions
- Standards support including PMML