Jan. 22, 2009 -
PRLog -- At the Open Source Meets Business (OSMB) congress from January 27th to 29th, 2009, in Nürnberg (Nuremberg) in Germany, the winner of the Open Source Business Award 2008, Rapid-I, will again contribute. On Tuesday, January 27th, 2009, 16:00h (4 PM), Rapid-I co-founder and CEO Ralf Klinkenberg gives a talk entitled „RapidMiner – Open Source Data Mining Delivering Predictions“
and presents details about Rapid-I’s Open Source Software RapidMiner. This talk gives an overview over the most important data mining applications and how companies word-wide successfully deploy them with RapidMiner. In addition, the business intelligence and data mining specialist Rapid-I will present its vision as well as the past and future development of the Open Source Project RapidMiner. Rapid-
I CEO Ralf Klinkenberg will be available for meetings and information during all three days of this congress.
The OSMB-2009 congress brings together open source companies and their open source products with numerous companies that either already successfully deploy open source software or that are considering to do so. A large number of talks given by companies from very diverse industry sectors give practical insights in the application of open source software in these companies and sectors.
Rapid-I is a provider of business intelligence, predictive analytics, data mining, text mining, and web mining software, solutions, and services offering its customers automatable intelligent data analysis of large amounts of data and text including automatically generated classification and forecasting systems. Rapid-
I won the highly rewarded Open Source Business Award 2008. The open source data mining specialist Rapid-I enables other companies to use the latest technology for intelligent data analysis and for the discovery of still unused company knowledge from existing data. Rapid-
I has a broad user and customer base in more than 40 countries including companies like Ford, Honda, Nokia, Miele, Philips, IBM, HP, Cisco, Merrill Lynch, BNP Paribas, Bank of America, mobilkom austria, Akzo Nobel, Aureus Pharma, PharmaDM, Cyprotex, Celera, Revere, LexisNexis, and Mitre as well as many small and mid-sized companies. Rapid-
I is headquartered in Dortmund, Germany. Besides of its since 2001 continuously improved data mining software RapidMiner, Rapid-I offers its customers a broad range of services including consulting, trainings, professional support, software development, customization, and extensions as well as complete data analysis services from a single source.
"The business year 2008 was a very successful one for Rapid-I." explains company co-founder and CEO Ingo Mierswa and adds "We doubled the number of employees and more than tripled the sales volume from 2007 to 2008 and we also expect a continued strong growth well above market average for 2009. In contrast to some venture-capital-
based US-American open source business intelligence companies, Rapid-I is 100% privately owned by the company founders and a rapidly growing and first of all profitable open source company.“
For companies and decision makers who want to get an idea of the potential of data mining in general or of the data mining software RapidMiner in particular for their enterprise, Rapid-I offers a quick introduction into this technology and its merits by providing consulting and training courses: In addition to introductory and application-
oriented courses for example into statistical forecasting, classification, regression, and clustering techniques, text mining, and web mining, Rapid-I also offers industry sector specific training courses on data mining in the production sector for predictive maintenance, machine failure avoidance, and quality control and optimization, on data mining for accounting, controlling, auditing, and fraud detection, on data mining for customer support, relationship management, marketing, and up- and cross-selling, as well as for the financial sector, i.e. for investment funds, banks, and insurance companies. There are also tailored courses for software developers who would like to integrate RapidMiner into their own products or would like to adapt or extend RapidMiner according to their needs. Upon request, training courses are also possible in-house at the customer site. Rapid-
I customers can make use of professional support via e-mail and telephone with guaranteed response times.
About RapidMiner:
RapidMiner ( www.RapidMiner.com ) is the leading open source data mining software. According to a poll of the major web portal for data mining and knowledge discovery, KDnuggets.com, in May 2008 among 347 data mining experts, RapidMiner is the most widely used open source data mining tool, the second most frequently employed software for data analysis overall. A study of the Technical University of Chemnitz presented at the international Data-Mining-
Cup 2007 (DMC-2007) compared the major open source data mining tools and found RapidMiner to be the leading open source data mining software outperforming the others especially with respect to its advanced technology and to its usability. Within its "Innovation Award 2008", the German initiative for small and mid-sized businesses ("Initiative Mittelstand")
awarded RapidMiner as one of the most innovative open source solutions. RapidMiner has thousands of users in more than 40 countries world-wide. During the last three years, RapidMiner was downloaded more than 350,000 times. RapidMiner provides more than 500 different modules for detecting patterns in data and for their 2D and 3D visualisation. RapidMiner supports data import from common data formats of other data mining tools, Excel sheets, SPSS files, all common databases, and unstructured text documents like news texts, e-mail messages, web pages, web blogs, PDF documents, as well as time series and audio data.
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Rapid-I provides predictive analytics, data mining, and text mining software, solutions, and services as well as intelligent analysis of large amounts of data including automatically generated classification and forecasting systems: www.rapid-i.com
