Tag: web

Use R for Business- Competition worth $ 20,000 #rstats

All you contest junkies, R lovers and general change the world people, here’s a new contest to use R in a business application

http://www.revolutionanalytics.com/news-events/news-room/2011/revolution-analytics-launches-applications-of-r-in-business-contest.php

REVOLUTION ANALYTICS LAUNCHES “APPLICATIONS OF R IN BUSINESS” CONTEST

$20,000 in Prizes for Users Solving Business Problems with R

 

PALO ALTO, Calif. – September 1, 2011 – Revolution Analytics, the leading commercial provider of R software, services and support, today announced the launch of its “Applications of R in Business” contest to demonstrate real-world uses of applying R to business problems. The competition is open to all R users worldwide and submissions will be accepted through October 31. The Grand Prize winner for the best application using R or Revolution R will receive $10,000.

The bonus-prize winner for the best application using features unique to Revolution R Enterprise – such as itsbig-data analytics capabilities or its Web Services API for R – will receive $5,000. A panel of independent judges drawn from the R and business community will select the grand and bonus prize winners. Revolution Analytics will present five honorable mention prize winners each with $1,000.

“We’ve designed this contest to highlight the most interesting use cases of applying R and Revolution R to solving key business problems, such as Big Data,” said Jeff Erhardt, COO of Revolution Analytics. “The ability to process higher-volume datasets will continue to be a critical need and we encourage the submission of applications using large datasets. Our goal is to grow the collection of online materials describing how to use R for business applications so our customers can better leverage Big Analytics to meet their analytical and organizational needs.”

To enter Revolution Analytics’ “Applications of R in Business” competition Continue reading “Use R for Business- Competition worth $ 20,000 #rstats”

Using Google Fusion Tables from #rstats

But after all that- I was quite happy to see Google Fusion Tables within Google Docs. Databases as a service ? Not quite but still quite good, and lets see how it goes.

https://www.google.com/fusiontables/DataSource?dsrcid=implicit&hl=en_US&pli=1

http://googlesystem.blogspot.com/2011/09/fusion-tables-new-google-docs-app.html

 

But what interests me more is

http://code.google.com/apis/fusiontables/docs/developers_guide.html

The Google Fusion Tables API is a set of statements that you can use to search for and retrieve Google Fusion Tables data, insert new data, update existing data, and delete data. The API statements are sent to the Google Fusion Tables server using HTTP GET requests (for queries) and POST requests (for inserts, updates, and deletes) from a Web client application. The API is language agnostic: you can write your program in any language you prefer, as long as it provides some way to embed the API calls in HTTP requests.

The Google Fusion Tables API does not provide the mechanism for submitting the GET and POST requests. Typically, you will use an existing code library that provides such functionality; for example, the code libraries that have been developed for the Google GData API. You can also write your own code to implement GET and POST requests.

Also see http://code.google.com/apis/fusiontables/docs/sample_code.html

 

Google Fusion Tables API Sample Code

Libraries

SQL API

Language Library Public repository Samples
Python Fusion Tables Python Client Library fusion-tables-client-python/ Samples
PHP Fusion Tables PHP Client Library fusion-tables-client-php/ Samples

Featured Samples

An easy way to learn how to use an API can be to look at sample code. The table above provides links to some basic samples for each of the languages shown. This section highlights particularly interesting samples for the Fusion Tables API.

SQL API

Language Featured samples API version
cURL
  • Hello, cURLA simple example showing how to use curl to access Fusion Tables.
 SQL API
Google Apps Script SQL API
Java
  • Hello, WorldA simple walkthrough that shows how the Google Fusion Tables API statements work.
  • OAuth example on fusion-tables-apiThe Google Fusion Tables team shows how OAuth authorization enables you to use the Google Fusion Tables API from a foreign web server with delegated authorization.
 SQL API
Python
  • Docs List ExampleDemonstrates how to:
    • List tables
    • Set permissions on tables
    • Move a table to a folder
 Docs List API
Android (Java)
  • Basic Sample ApplicationDemo application shows how to create a crowd-sourcing application that allows users to report potholes and save the data to a Fusion Table.
 SQL API
JavaScript – FusionTablesLayer Using the FusionTablesLayer, you can display data on a Google Map

Also check out FusionTablesLayer Builder, which generates all the code necessary to include a Google Map with a Fusion Table Layer on your own website.

 FusionTablesLayer, Google Maps API
JavaScript – Google Chart Tools Using the Google Chart Tools, you can request data from Fusion Tables to use in visualizations or to display directly in an HTML page. Note: responses are limited to 500 rows of data.

 Google Chart Tools

External Resources

Google Fusion Tables is dedicated to providing code examples that illustrate typical uses, best practices, and really cool tricks. If you do something with the Google Fusion Tables API that you think would be interesting to others, please contact us at googletables-feedback@google.com about adding your code to our Examples page.

  • Shape EscapeA tool for uploading shape files to Fusion Tables.
  • GDALOGR Simple Feature Library has incorporated Fusion Tables as a supported format.
  • Arc2CloudArc2Earth has included support for upload to Fusion Tables via Arc2Cloud.
  • Java and Google App EngineODK Aggregate is an AppEngine application by the Open Data Kit team, uses Google Fusion Tables to store survey data that is collected through input forms on Android mobile phones. Notable code:
  • R packageAndrei Lopatenko has written an R interface to Fusion Tables so Fusion Tables can be used as the data store for R.
  • RubySimon Tokumine has written a Ruby gem for access to Fusion Tables from Ruby.

 

Updated-You can use Google Fusion Tables from within R from http://andrei.lopatenko.com/rstat/fusion-tables.R

 

ft.connect <- function(username, password) {
  url = "https://www.google.com/accounts/ClientLogin";
  params = list(Email = username, Passwd = password, accountType="GOOGLE", service= "fusiontables", source = "R_client_API")
 connection = postForm(uri = url, .params = params)
 if (length(grep("error", connection, ignore.case = TRUE))) {
 	stop("The wrong username or password")
 	return ("")
 }
 authn = strsplit(connection, "\nAuth=")[[c(1,2)]]
 auth = strsplit(authn, "\n")[[c(1,1)]]
 return (auth)
}

ft.disconnect <- function(connection) {
}

ft.executestatement <- function(auth, statement) {
      url = "http://tables.googlelabs.com/api/query"
      params = list( sql = statement)
      connection.string = paste("GoogleLogin auth=", auth, sep="")
      opts = list( httpheader = c("Authorization" = connection.string))
      result = postForm(uri = url, .params = params, .opts = opts)
      if (length(grep("<HTML>\n<HEAD>\n<TITLE>Parse error", result, ignore.case = TRUE))) {
      	stop(paste("incorrect sql statement:", statement))
      }
      return (result)
}

ft.showtables <- function(auth) {
   url = "http://tables.googlelabs.com/api/query"
   params = list( sql = "SHOW TABLES")
   connection.string = paste("GoogleLogin auth=", auth, sep="")
   opts = list( httpheader = c("Authorization" = connection.string))
   result = getForm(uri = url, .params = params, .opts = opts)
   tables = strsplit(result, "\n")
   tableid = c()
   tablename = c()
   for (i in 2:length(tables[[1]])) {
     	str = tables[[c(1,i)]]
   	    tnames = strsplit(str,",")
   	    tableid[i-1] = tnames[[c(1,1)]]
   	    tablename[i-1] = tnames[[c(1,2)]]
   	}
   	tables = data.frame( ids = tableid, names = tablename)
    return (tables)
}

ft.describetablebyid <- function(auth, tid) {
   url = "http://tables.googlelabs.com/api/query"
   params = list( sql = paste("DESCRIBE", tid))
   connection.string = paste("GoogleLogin auth=", auth, sep="")
   opts = list( httpheader = c("Authorization" = connection.string))
   result = getForm(uri = url, .params = params, .opts = opts)
   columns = strsplit(result,"\n")
   colid = c()
   colname = c()
   coltype = c()
   for (i in 2:length(columns[[1]])) {
     	str = columns[[c(1,i)]]
   	    cnames = strsplit(str,",")
   	    colid[i-1] = cnames[[c(1,1)]]
   	    colname[i-1] = cnames[[c(1,2)]]
   	    coltype[i-1] = cnames[[c(1,3)]]
   	}
   	cols = data.frame(ids = colid, names = colname, types = coltype)
    return (cols)
}

ft.describetable <- function (auth, table_name) {
   table_id = ft.idfromtablename(auth, table_name)
   result = ft.describetablebyid(auth, table_id)
   return (result)
}

ft.idfromtablename <- function(auth, table_name) {
    tables = ft.showtables(auth)
	tableid = tables$ids[tables$names == table_name]
	return (tableid)
}

ft.importdata <- function(auth, table_name) {
	tableid = ft.idfromtablename(auth, table_name)
	columns = ft.describetablebyid(auth, tableid)
	column_spec = ""
	for (i in 1:length(columns)) {
		column_spec = paste(column_spec, columns[i, 2])
		if (i < length(columns)) {
			column_spec = paste(column_spec, ",", sep="")
		}
	}
	mdata = matrix(columns$names,
	              nrow = 1, ncol = length(columns),
	              dimnames(list(c("dummy"), columns$names)), byrow=TRUE)
	select = paste("SELECT", column_spec)
	select = paste(select, "FROM")
	select = paste(select, tableid)
	result = ft.executestatement(auth, select)
    numcols = length(columns)
    rows = strsplit(result, "\n")
    for (i in 3:length(rows[[1]])) {
    	row = strsplit(rows[[c(1,i)]], ",")
    	mdata = rbind(mdata, row[[1]])
   	}
   	output.frame = data.frame(mdata[2:length(mdata[,1]), 1])
   	for (i in 2:ncol(mdata)) {
   		output.frame = cbind(output.frame, mdata[2:length(mdata[,i]),i])
   	}
   	colnames(output.frame) = columns$names
    return (output.frame)
}

quote_value <- function(value, to_quote = FALSE, quote = "'") {
	 ret_value = ""
     if (to_quote) {
     	ret_value = paste(quote, paste(value, quote, sep=""), sep="")
     } else {
     	ret_value = value
     }
     return (ret_value)
}

converttostring <- function(arr, separator = ", ", column_types) {
	con_string = ""
	for (i in 1:(length(arr) - 1)) {
		value = quote_value(arr[i], column_types[i] != "number")
		con_string = paste(con_string, value)
	    con_string = paste(con_string, separator, sep="")
	}

    if (length(arr) >= 1) {
    	value = quote_value(arr[length(arr)], column_types[length(arr)] != "NUMBER")
    	con_string = paste(con_string, value)
    }
}

ft.exportdata <- function(auth, input_frame, table_name, create_table) {
	if (create_table) {
       create.table = "CREATE TABLE "
       create.table = paste(create.table, table_name)
       create.table = paste(create.table, "(")
       cnames = colnames(input_frame)
       for (columnname in cnames) {
         create.table = paste(create.table, columnname)
    	 create.table = paste(create.table, ":string", sep="")
    	   if (columnname != cnames[length(cnames)]){
    		  create.table = paste(create.table, ",", sep="")
           }
       }
      create.table = paste(create.table, ")")
      result = ft.executestatement(auth, create.table)
    }
    if (length(input_frame[,1]) > 0) {
    	tableid = ft.idfromtablename(auth, table_name)
	    columns = ft.describetablebyid(auth, tableid)
	    column_spec = ""
	    for (i in 1:length(columns$names)) {
		   column_spec = paste(column_spec, columns[i, 2])
		   if (i < length(columns$names)) {
			  column_spec = paste(column_spec, ",", sep="")
		   }
	    }
    	insert_prefix = "INSERT INTO "
    	insert_prefix = paste(insert_prefix, tableid)
    	insert_prefix = paste(insert_prefix, "(")
    	insert_prefix = paste(insert_prefix, column_spec)
    	insert_prefix = paste(insert_prefix, ") values (")
    	insert_suffix = ");"
    	insert_sql_big = ""
    	for (i in 1:length(input_frame[,1])) {
    		data = unlist(input_frame[i,])
    		values = converttostring(data, column_types  = columns$types)
    		insert_sql = paste(insert_prefix, values)
    		insert_sql = paste(insert_sql, insert_suffix) ;
    		insert_sql_big = paste(insert_sql_big, insert_sql)
    		if (i %% 500 == 0) {
    			ft.executestatement(auth, insert_sql_big)
    			insert_sql_big = ""
    		}
    	}
        ft.executestatement(auth, insert_sql_big)
    }
}

Interview Scott Gidley CTO and Founder, DataFlux

Here is an interview with Scott Gidley, CTO and co-founder of leading data quality ccompany DataFlux . DataFlux is a part of SAS Institute and in 2011 acquired Baseline Consulting besides launching the latest version of their Master Data Management  product. Continue reading “Interview Scott Gidley CTO and Founder, DataFlux”

Interview Beth Schultz Editor AllAnalytics.com

Here is an interview with Beth Scultz Editor in Chief, AllAnalytics.com .

Allanalytics.com http://www.allanalytics.com/ is the new online community on Predictive Analytics, and its a bit different in emphasizing quality more than just quantity. Beth is veteran in tech journalism and communities.

Ajay-Describe your journey in technology journalism and communication. What are the other online communities that you have been involved with?

Beth- I’m a longtime IT journalist, having begun my career covering the telecommunications industry at the brink of AT&T’s divestiture — many eons ago. Over the years, I’ve covered the rise of internal corporate networking; the advent of the Internet and creation of the Web for business purposes; the evolution of Web technology for use in building intranets, extranets, and e-commerce sites; the move toward a highly dynamic next-generation IT infrastructure that we now call cloud computing; and development of myriad enterprise applications, including business intelligence and the analytics surrounding them. I have been involved in developing online B2B communities primarily around next-generation enterprise IT infrastructure and applications. In addition, Shawn Hessinger, our community editor, has been involved in myriad Web sites aimed at creating community for small business owners.

 Ajay- Technology geeks get all the money while journalists get a story. Comments please

Beth- Great technology geeks — those being the ones with technology smarts as well as business savvy — do stand to make a lot of money. And some pursue that to all ends (with many entrepreneurs gunning for the acquisition) while others more or less fall into it. Few journalists, at least few tech journalists, have big dollars in mind. The gratification for journalists comes in being able to meet these folks, hear and deliver their stories — as appropriate — and help explain what makes this particular technology geek developing this certain type of product or service worth paying attention to.

 Ajay- Describe what you are trying to achieve with the All Analytics community and how it seeks to differentiate itself with other players in this space.

 Beth- With AllAnaltyics.com, we’re concentrating on creating the go-to site for CXOs, IT professionals, line-of-business managers, and other professionals to share best practices, concrete experiences, and research about data analytics, business intelligence, information optimization, and risk management, among many other topics. We differentiate ourself by featuring excellent editorial content from a top-notch group of bloggers, access to industry experts through weekly chats, ongoing lively and engaging message board discussions, and biweekly debates.

We’re a new property, and clearly in rapid building mode. However, we’ve already secured some of the industry’s most respected BI/analytics experts to participate as bloggers. For example, a small sampling of our current lineup includes the always-intrigueing John Barnes, a science fiction novelist and statistics guru; Sandra Gittlen, a longtime IT journalist with an affinity for BI coverage; Olivia Parr-Rud, an internationally recognized expert in BI and organizational alignment; Tom Redman, a well-known data-quality expert; and Steve Williams, a leading BI strategy consultant. I blog daily as well, and in particular love to share firsthand experiences of how organizations are benefiting from the use of BI, analytics, data warehousing, etc. We’ve featured inside looks at analytics initiatives at companies such as 1-800-Flowers.com, Oberweis Dairy, the Cincinnati Zoo & Botanical Garden, and Thomson Reuters, for example.

In addition, we’ve hosted instant e-chats with Web and social media experts Joe Stanganelli and Pierre DeBois, and this Friday, Aug. 26, at 3 p.m. ET we’ll be hosting an e-chat with Marshall Sponder, Web metrics guru and author of the newly published book, Social Media Analytics: Effective Tools for Building, Interpreting, and Using Metrics. (Readers interested in participating in the chat do need to fill out a quick registration form, available here http://www.allanalytics.com/register.asp . The chat is available here http://www.allanalytics.com/messages.asp?piddl_msgthreadid=241039&piddl_msgid=439898#msg_439898 .

Experts participating in our biweekly debate series, called Point/Counterpoint, have broached topics such as BI in the cloud, mobile BI and whether an analytics culture is truly possible to build.

Ajay-  What are some tips you would like to share about writing tech stories to aspiring bloggers.

Beth- I suppose my best advice is this: Don’t write about technology for technology’s sake. Always strive to tell the audience why they should care about a particular technology, product, or service. How might a reader use it to his or her company’s advantage, and what are the potential benefits? Improved productivity, increased revenue, better customer service? Providing anecdotal evidence goes a long way toward delivering that message, as well.

Ajay- What are the other IT world websites that have made a mark on the internet.

Beth- I’d be remiss if I didn’t give a shout out to UBM TechWeb sites, including InformationWeek, which has long charted the use of IT within the enterprise; Dark Reading, a great source for folks interested in securing an enterprise’s information assets; and Light Reading, which takes the pulse of the telecom industry.

 Biography- 

Beth Schultz has more than two decades of experience as an IT writer and editor. Most recently, she brought her expertise to bear writing thought-provoking editorial and marketing materials on a variety of technology topics for leading IT publications and industry players. Previously, she oversaw multimedia content development, writing and editing for special feature packages at Network World. Beth has a keen ability to identify business and technology trends, developing expertise through in-depth analysis and early-adopter case studies. Over the years, she has earned more than a dozen national and regional editorial excellence awards for special issues from American Business Media, American Society of Business Press Editors, Folio.net, and others.

 

Using #Rstats for online data access

There are multiple packages in R to read data straight from online datasets.
These are as follows- Continue reading “Using #Rstats for online data access”

Cloud Computing by Windows , Amazon and Google for free

Some ways to test and use cloud computing for free for yourself-

  1. Windows Azure
  2. Amazon Ec2
  3. Google Storage

The folks at Microsoft Azure announced a 90 day free trial Continue reading “Cloud Computing by Windows , Amazon and Google for free”

Interview Rapid-I -Ingo Mierswa and Simon Fischer

Here is an interview with Dr Ingo Mierswa , CEO of Rapid -I and Dr Simon Fischer, Head R&D. Rapid-I makes the very popular software Rapid Miner – perhaps one of the earliest leading open source software in business analytics and business intelligence. It is quite easy to use, deploy and with it’s extensions and innovations (including compatibility with R )has continued to grow tremendously through the years.

In an extensive interview Ingo and Simon talk about algorithms marketplace, extensions , big data analytics, hadoop, mobile computing and use of the graphical user interface in analytics.

Special Thanks to Nadja from Rapid I communication team for helping coordinate this interview.( Statuary Blogging Disclosure- Rapid I is a marketing partner with Decisionstats as per the terms in https://decisionstats.com/privacy-3/)

Ajay- Describe your background in science. What are the key lessons that you have learnt while as scientific researcher and what advice would you give to new students today.

Ingo: My time as researcher really was a great experience which has influenced me a lot. I have worked at the AI lab of Prof. Dr. Katharina Morik, one of the persons who brought machine learning and data mining to Europe. Katharina always believed in what we are doing, encouraged us and gave us the space for trying out new things. Funnily enough, I never managed to use my own scientific results in any real-life project so far but I consider this as a quite common gap between science and the “real world”. At Rapid-I, however, we are still heavily connected to the scientific world and try to combine the best of both worlds: solving existing problems with leading-edge technologies.

Simon: In fact, during my academic career I have not worked in the field of data mining at all. I worked on a field some of my colleagues would probably even consider boring, and that is theoretical computer science. To be precise, my research was in the intersection of game theory and network theory. During that time, I have learnt a lot of exciting things, none of which had any business use. Still, I consider that a very valuable experience. When we at Rapid-I hire people coming to us right after graduating, I don’t care whether they know the latest technology with a fancy three-letter acronym – that will be forgotten more quickly than it came. What matters is the way you approach new problems and challenges. And that is also my recommendation to new students: work on whatever you like, as long as you are passionate about it and it brings you forward.

Ajay-  How is the Rapid Miner Extensions marketplace moving along. Do you think there is a scope for people to say create algorithms in a platform like R , and then offer that algorithm as an app for sale just like iTunes or Android apps.

 Simon: Well, of course it is not going to be exactly like iTunes or Android apps are, because of the more business-orientated character. But in fact there is a scope for that, yes. We have talked to several developers, e.g., at our user conference RCOMM, and several people would be interested in such an opportunity. Companies using data mining software need supported software packages, not just something they downloaded from some anonymous server, and that is only possible through a platform like the new Marketplace. Besides that, the marketplace will not only host commercial extensions. It is also meant to be a platform for all the developers that want to publish their extensions to a broader community and make them accessible in a comfortable way. Of course they could just place them on their personal Web pages, but who would find them there? From the Marketplace, they are installable with a single click.

Ingo: What I like most about the new Rapid-I Marketplace is the fact that people can now get something back for their efforts. Developing a new algorithm is a lot of work, in some cases even more that developing a nice app for your mobile phone. It is completely accepted that people buy apps from a store for a couple of Dollars and I foresee the same for sharing and selling algorithms instead of apps. Right now, people can already share algorithms and extensions for free, one of the next versions will also support selling of those contributions. Let’s see what’s happening next, maybe we will add the option to sell complete RapidMiner workflows or even some data pools…

Ajay- What are the recent features in Rapid Miner that support cloud computing, mobile computing and tablets. How do you think the landscape for Big Data (over 1 Tb ) is changing and how is Rapid Miner adapting to it.

Simon: These are areas we are very active in. For instance, we have an In-Database-Mining Extension that allows the user to run their modelling algorithms directly inside the database, without ever loading the data into memory. Using analytic databases like Vectorwise or Infobright, this technology can really boost performance. Our data mining server, RapidAnalytics, already offers functionality to send analysis processes into the cloud. In addition to that, we are currently preparing a research project dealing with data mining in the cloud. A second project is targeted towards the other aspect you mention: the use of mobile devices. This is certainly a growing market, of course not for designing and running analyses, but for inspecting reports and results. But even that is tricky: When you have a large screen you can display fancy and comprehensive interactive dashboards with drill downs and the like. On a mobile device, that does not work, so you must bring your reports and visualizations very much to the point. And this is precisely what data mining can do – and what is hard to do for classical BI.

Ingo: Then there is Radoop, which you may have heard of. It uses the Apache Hadoop framework for large-scale distributed computing to execute RapidMiner processes in the cloud. Radoop has been presented at this year’s RCOMM and people are really excited about the combination of RapidMiner with Hadoop and the scalability this brings.

 Ajay- Describe the Rapid Miner analytics certification program and what steps are you taking to partner with academic universities.

Ingo: The Rapid-I Certification Program was created to recognize professional users of RapidMiner or RapidAnalytics. The idea is that certified users have demonstrated a deep understanding of the data analysis software solutions provided by Rapid-I and how they are used in data analysis projects. Taking part in the Rapid-I Certification Program offers a lot of benefits for IT professionals as well as for employers: professionals can demonstrate their skills and employers can make sure that they hire qualified professionals. We started our certification program only about 6 months ago and until now about 100 professionals have been certified so far.

Simon: During our annual user conference, the RCOMM, we have plenty of opportunities to talk to people from academia. We’re also present at other conferences, e.g. at ECML/PKDD, and we are sponsoring data mining challenges and grants. We maintain strong ties with several universities all over Europe and the world, which is something that I would not want to miss. We are also cooperating with institutes like the ITB in Dublin during their training programmes, e.g. by giving lectures, etc. Also, we are leading or participating in several national or EU-funded research projects, so we are still close to academia. And we offer an academic discount on all our products 🙂

Ajay- Describe the global efforts in making Rapid Miner a truly international software including spread of developers, clients and employees.

Simon: Our clients already are very international. We have a partner network in America, Asia, and Australia, and, while I am responding to these questions, we have a training course in the US. Developers working on the core of RapidMiner and RapidAnalytics, however, are likely to stay in Germany for the foreseeable future. We need specialists for that, and it would be pointless to spread the development team over the globe. That is also owed to the agile philosophy that we are following.

Ingo: Simon is right, Rapid-I already is acting on an international level. Rapid-I now has more than 300 customers from 39 countries in the world which is a great result for a young company like ours. We are of course very strong in Germany and also the rest of Europe, but also concentrate on more countries by means of our very successful partner network. Rapid-I continues to build this partner network and to recruit dynamic and knowledgeable partners and in the future. However, extending and acting globally is definitely part of our strategic roadmap.

Biography–

Dr. Ingo Mierswa is working as Chief Executive Officer (CEO) of Rapid-I. He has several years of experience in project management, human resources management, consulting, and leadership including eight years of coordinating and leading the multi-national RapidMiner developer team with about 30 developers and contributors world-wide. He wrote his Phd titled “Non-Convex and Multi-Objective Optimization for Numerical Feature Engineering and Data Mining” at the University of Dortmund under the supervision of Prof. Morik.

Dr. Simon Fischer is heading the research & development at Rapid-I. His interests include game theory and networks, the theory of evolutionary algorithms (e.g. on the Ising model), and theoretical and practical aspects of data mining. He wrote his PhD in Aachen where he worked in the project “Design and Analysis of Self-Regulating Protocols for Spectrum Assignment” within the excellence cluster UMIC. Before, he was working on the vtraffic project within the DFG Programme 1126 “Algorithms for large and complex networks”.

http://rapid-i.com/content/view/181/190/ tells you more on the various types of Rapid Miner licensing for enterprise, individual and developer versions.

(Note from Ajay- to receive an early edition invite to Radoop, click here http://radoop.eu/z1sxe)