RapidMiner launches extensions marketplace

For some time now, I had been hoping for a place where new package or algorithm developers get at least a fraction of the money that iPad or iPhone application developers get. Rapid Miner has taken the lead in establishing a marketplace for extensions. Is there going to be paid extensions as well- I hope so!!

This probably makes it the first “app” marketplace in open source and the second app marketplace in analytics after salesforce.com

It is hard work to think of new algols, and some of them can really be usefull.

Can we hope for #rstats marketplace where people downloading say ggplot3.0 atleast get a prompt to donate 99 cents per download to Hadley Wickham’s Amazon wishlist. http://www.amazon.com/gp/registry/1Y65N3VFA613B

Do you think it is okay to pay 99 cents per iTunes song, but not pay a cent for open source software.

I dont know- but I am just a capitalist born in a country that was socialist for the first 13 years of my life. Congratulations once again to Rapid Miner for innovating and leading the way.

http://rapid-i.com/component/option,com_myblog/show,Rapid-I-Marketplace-Launched.html/Itemid,172

RapidMinerMarketplaceExtensions 30 May 2011
Rapid-I Marketplace Launched by Simon Fischer

Over the years, many of you have been developing new RapidMiner Extensions dedicated to a broad set of topics. Whereas these extensions are easy to install in RapidMiner – just download and place them in the plugins folder – the hard part is to find them in the vastness that is the Internet. Extensions made by ourselves at Rapid-I, on the other hand,  are distributed by the update server making them searchable and installable directly inside RapidMiner.

We thought that this was a bit unfair, so we decieded to open up the update server to the public, and not only this, we even gave it a new look and name. The Rapid-I Marketplace is available in beta mode at http://rapidupdate.de:8180/ . You can use the Web interface to browse, comment, and rate the extensions, and you can use the update functionality in RapidMiner by going to the preferences and entering http://rapidupdate.de:8180/UpdateServer/ as the update server URL. (Once the beta test is complete, we will change the port back to 80 so we won’t have any firewall problems.)

As an Extension developer, just register with the Marketplace and drop me an email (fischer at rapid-i dot com) so I can give you permissions to upload your own extension. Upload is simple provided you use the standard RapidMiner Extension build process and will boost visibility of your extension.

Looking forward to see many new extensions there soon!

Disclaimer- Decisionstats is a partner of Rapid Miner. I have been liking the software for a long long time, and recently agreed to partner with them just like I did with KXEN some years back, and with Predictive AnalyticsConference, and Aster Data until last year.

I still think Rapid Miner is a very very good software,and a globally created software after SAP.

Here is the actual marketplace

http://rapidupdate.de:8180/UpdateServer/faces/index.xhtml

Welcome to the Rapid-I Marketplace Public Beta Test

The Rapid-I Marketplace will soon replace the RapidMiner update server. Using this marketplace, you can share your RapidMiner extensions and make them available for download by the community of RapidMiner users. Currently, we are beta testing this server. If you want to use this server in RapidMiner, you must go to the preferences and enter http://rapidupdate.de:8180/UpdateServer for the update url. After the beta test, we will change the port back to 80, which is currently occupied by the old update server. You can test the marketplace as a user (downloading extensions) and as an Extension developer. If you want to publish your extension here, please let us know via the contact form.

Hot Downloads
«« « 1 2 3 » »»
[Icon]The Image Processing Extension provides operators for handling image data. You can extract attributes describing colour and texture in the image, you can make several transformation of a image data which allows you to perform segmentation and detection of suspicious areas in image data.The extension provides many of image transformation and extraction operators ranging from Wavelet Decomposition, Hough Circle to Block Difference of Inverse probabilities.

[Icon]RapidMiner is unquestionably the world-leading open-source system for data mining. It is available as a stand-alone application for data analysis and as a data mining engine for the integration into own products. Thousands of applications of RapidMiner in more than 40 countries give their users a competitive edge.

  • Data IntegrationAnalytical ETLData Analysis, and Reporting in one single suite
  • Powerful but intuitive graphical user interface for the design of analysis processes
  • Repositories for process, data and meta data handling
  • Only solution with meta data transformation: forget trial and error and inspect results already during design time
  • Only solution which supports on-the-fly error recognition and quick fixes
  • Complete and flexible: Hundreds of data loading, data transformation, data modeling, and data visualization methods
[Icon]All modeling methods and attribute evaluation methods from the Weka machine learning library are available within RapidMiner. After installing this extension you will get access to about 100 additional modelling schemes including additional decision trees, rule learners and regression estimators.This extension combines two of the most widely used open source data mining solutions. By installing it, you can extend RapidMiner to everything what is possible with Weka while keeping the full analysis, preprocessing, and visualization power of RapidMiner.

[Icon]Finally, the two most widely used data analysis solutions – RapidMiner and R – are connected. Arbitrary R models and scripts can now be directly integrated into the RapidMiner analysis processes. The new R perspective offers the known R console together with the great plotting facilities of R. All variables and R scripts can be organized in the RapidMiner Repository.A directly included online help and multi-line editing makes the creation of R scripts much more comfortable.

AsterData still alive;/launches SQL-MapReduce Developer Portal

so apparantly ole client AsterData continues to thrive under gentle touch of Terrific Data

———————————————————————————————————————————————————

Aster Data today launched the SQL-MapReduce Developer Portal, a new online community for data scientists and analytic developers. For your convenience, I copied the release below and it can also be found here. Please let me know if you have any questions or if there is anything else I can help you with.

Sara Korolevich

Point Communications Group for Aster Data

sarak@pointcgroup.com

Office: 602.279.1137

Mobile: 623.326.0881

Teradata Accelerates Big Data Analytics with First Collaborative Community for SQL-MapReduce®

New online community for data scientists and analytic developers enables development and sharing of powerful MapReduce analytics


San Carlos, California – Teradata Corporation (NYSE:TDC) today announced the launch of the Aster Data SQL-MapReduce® Developer Portal. This portal is the first collaborative online developer community for SQL-MapReduce analytics, an emerging framework for processing non-relational data and ultra-fast analytics.

“Aster Data continues to deliver on its unique vision for powerful analytics with a rich set of tools to make development of those analytics quick and easy,” said Tasso Argyros, vice president of Aster Data Marketing and Product Management, Teradata Corporation. “This new developer portal builds on Aster Data’s continuing SQL-MapReduce innovation, leveraging the flexibility and power of SQL-MapReduce for analytics that were previously impossible or impractical.”

The developer portal showcases the power and flexibility of Aster Data’s SQL-MapReduce – which uniquely combines standard SQL with the popular MapReduce distributed computing technology for processing big data – by providing a collaborative community for sharing SQL-MapReduce expert insights in addition to sharing SQL-MapReduce analytic functions and sample code. Data scientists, quantitative analysts, and developers can now leverage the experience, knowledge, and best practices of a community of experts to easily harness the power of SQL-MapReduce for big data analytics.

A recent report from IDC Research, “Taking Care of Your Quants: Focusing Data Warehousing Resources on Quantitative Analysts Matters,” has shown that by enabling data scientists with the tools to harness emerging types and sources of data, companies create significant competitive advantage and become leaders in their respective industry.

“The biggest positive differences among leaders and the rest come from the introduction of new types of data,” says Dan Vesset, program vice president, Business Analytics Solutions, IDC Research. “This may include either new transactional data sources or new external data feeds of transactional or multi-structured interactional data — the latter may include click stream or other data that is a by-product of social networking.”

Vesset goes on to say, “Aster Data provides a comprehensive platform for analytics and their SQL-MapReduce Developer Portal provides a community for sharing best practices and functions which can have an even greater impact to an organization’s business.”

With this announcement Aster Data extends its industry leadership in delivering the most comprehensive analytic platform for big data analytics — not only capable of processing massive volumes of multi-structured data, but also providing an extensive set of tools and capabilities that make it simple to leverage the power of MapReduce analytics. The Aster Data

SQL-MapReduce Developer Portal brings the power of SQL-MapReduce accessible to data scientists, quantitative analysis, and analytic developers by making it easy to share and collaborate with experts in developing SQL-MapReduce analytics. This portal builds on Aster Data’s history of SQL-MapReduce innovations, including:

  • The first deep integration of SQL with MapReduce
  • The first MapReduce support for .NET
  • The first integrated development environment, Aster Data
    Developer Express
  • A comprehensive suite of analytic functions, Aster Data
    Analytic Foundation

Aster Data’s patent-pending SQL-MapReduce enables analytic applications and functions that can deliver faster, deeper insights on terabytes to petabytes of data. These applications are implemented using MapReduce but delivered through standard SQL and business intelligence (BI) tools.

SQL-MapReduce makes it possible for data scientists and developers to empower business analysts with the ability to make informed decisions, incorporating vast amounts of data, regardless of query complexity or data type. Aster Data customers are using SQL-MapReduce for rich analytics including analytic applications for social network analysis, digital marketing optimization, and on-the-fly fraud detection and prevention.

“Collaboration is at the core of our success as one of the leading providers, and pioneers of social software,” said Navdeep Alam, director of Data Architecture at Mzinga. “We are pleased to be one of the early members of The Aster Data SQL-MapReduce Developer Portal, which will allow us the ability to share and leverage insights with others in using big data analytics to attain a deeper understanding of customers’ behavior and create competitive advantage for our business.”

SQL-MapReduce is one of the core capabilities within Aster Data’s flagship product. Aster DatanCluster™ 4.6, the industry’s first massively parallel processing (MPP) analytic platform has an integrated analytics engine that stores and processes both relational and non-relational data at scale. With Aster Data’s unique analytics framework that supports both SQL and
SQL-MapReduce™, customers benefit from rich, new analytics on large data volumes with complex data types. Aster Data analytic functions are embedded within the analytic platform and processed locally with data, which allows for faster data exploration. The SQL-MapReduce framework provides scalable fault-tolerance for new analytics, providing users with superior reliability, regardless of number of users, query size, or data types.


About Aster Data
Aster Data is a market leader in big data analytics, enabling the powerful combination of cost-effective storage and ultra-fast analysis of new sources and types of data. The Aster Data nCluster analytic platform is a massively parallel software solution that embeds MapReduce analytic processing with data stores for deeper insights on new data sources and types to deliver new analytic capabilities with breakthrough performance and scalability. Aster Data’s solution utilizes Aster Data’s patent-pending SQL-MapReduce to parallelize processing of data and applications and deliver rich analytic insights at scale. Companies including Barnes & Noble, Intuit, LinkedIn, Akamai, and MySpace use Aster Data to deliver applications such as digital marketing optimization, social network and relationship analysis, and fraud detection and prevention.


About Teradata
Teradata is the world’s leader in data warehousing and integrated marketing management through itsdatabase softwaredata warehouse appliances, and enterprise analytics. For more information, visitteradata.com.

# # #

Teradata is a trademark or registered trademark of Teradata Corporation in the United States and other countries.

TeraData buys AsterData for 260+ million $

Balance sheet venetian method
Image via Wikipedia

This just in! Big party in San Carlos this weekend.

Teradata is acquiring Aster Data‘s business, including its intellectual property and technology product line, through a merger transaction. Teradata plans to support Aster Data’s customers and integrate its employees immediately upon completion of the acquisition, which is expected to occur in the second quarter of 2011. Teradata acquired an 11 percent ownership interest in Aster Data in September 2010, and has agreed to pay an additional $263 million for the remaining ownership interest, net of debt and other expenses. In addition, through this acquisition, Teradata will obtain approximately $21 million of cash which Aster Data is expected to have on its balance sheet at closing.

http://www.asterdata.com/news/110303-Teradata-to-Acquire-Aster-Data.php

 

AsterData partners with Tableau

This chart represents several constituent comp...
Image via Wikipedia

Tableau which has been making waves recntly with its great new data visualization tool announced a partner with my old friends at AsterData. Its really cool piece of data vis and very very fast on the desktop- so I can imagine what speed it can help with AsterData’s MPP Row and Column Zingbang AND Parallel Analytical Functions

Tableau and AsterData also share the common Stanfordian connection (but it seems software is divided quite equally between Stanford, Hardvard Dropouts and North Carolina )

It remains to be seen in this announcement how much each company  can leverage the partnership or whether it turns like the SAS Institute- AsterData partnership last year or whether it is just to announce connectors in their software to talk to each other.

See a Tableau vis at

http://public.tableausoftware.com/views/geographyofdiabetes/Dashboard2?:embed=yes&:toolbar=yes

AsterData remains the guys with the potential but I would be wrong to say MapReduceSQL is as hot in December 2010 as it was in June 2009- and the elephant in the room would be Hadoop. That and Google’s continued shyness from encashing its principal comptency of handling Big Data (but hush – I signed a NDA with the Google Prediction API– so things maaaay change very rapidly on ahem that cloud)

Disclaimer- AsterData was my internship sponsor during my winter training while at Univ of  Tenn.

 

Interesting Interview with Quentin G,AsterData

Here is an interesting interview with Quentin G, CEO AsterData, Marketing trumpeting aside apart-the insights on the whats next vision thing are quite good.

Sourcehttp://www.arnoldit.com/search-wizards-speak/aster-data.html

As you look down the road, what are the three major challenges you see for vendors who keep trying to solve big data and other “now” problems with old tools?

Old tools and traditional architectures cannot scale effectively to handle massive data volumes that reach 100’s of terabytes nor can they effectively process large data volumes in a high performance manner. Further, they are restricted to what SQL querying allows. The three challenges I have noted are:

First, performance, specifically, poor performance on large data volumes and heavy workloads: The pre-existing systems rely on storing data in a traditional DBMS or data warehouse and then extracting a sample of data to a separate processing tier. This greatly restricts data insights and analytics as only a sample of data is analyzed and understood.  As more data is stored in these systems they suffer from performance degradation as more users try to access the system concurrently. Additionally moving masses of data out of the traditional DBMS to a separate processing tier adds latency and slows down analytics and response times. This pre-existing architecture greatly limits performance especially as data sizes grow.

Second, limited analytics: Pre-existing systems rely mostly on SQL for data querying and analysis. SQL poses several limitations and is not suited for ad hoc querying, deep data exploration and a range of other analytics. MapReduce overcomes the limitations of SQL and SQL-MapReduce in particular opens up a new class of analytics that cannot be achieved with SQL alone.

And, third, limitations of types of data that can be stored and analyzed: Traditional systems are not designed for non-relational or unstructured data. New solutions such as Aster Data’s are designed from the ground up to handle both relational and non-relational data. Organizations want to store and process a range of data types and do this in a single platform. New solutions allow for different data types to be handled in a single platform whereas pre-existing architectures and solutions are specialized around a single data type or format – this restricts the diversity of analytics that can be performed on these systems.

Read the whole interview at –http://www.arnoldit.com/search-wizards-speak/aster-data.html

Speaking of which- there is a new webinar by Merv Adrian (interview on Decisionstats) and Colin White-

 

http://now.eloqua.com/es.asp?s=1015&e=1862&elq=9ec9b73872e849b88d2943cca920acda

and from the famous AOL website- a profile of AsterData’s money flow which kind of hints at an IPO two years onwards-

http://www.crunchbase.com/company/aster-data-systems

Cloudera and Aster Data partner up

Basically making it easier for data to move between the two systems Hadoop (Cloudera) and Aster’s Analytics (MapReduce/SQL)-

From the press release-http://goo.gl/vgsr

today announced an agreement that unites Cloudera Distribution for Hadoop (CDH) with Aster Data nCluster. The integration enables customers to leverage MPP platforms for large-scale data processing, management and analytics across structured and unstructured formats to analyze massive amounts of data for deeper business insight.

Cloudera is building a massively parallel, two-way connector for high-speed movement of data between CDH and Aster Data nCluster. The connector will be supported as part of Cloudera Enterprise.

AsterData gets $30 mill in funding

From the press release, the maker of Map Reduce based BI software gets 30 mill $ as Series C funding. Given the valuation recently by IBM to Netezza, AsterData seems set to cross the Billion Dollar valuation within the next 18-24 months IMO

Aster Data Closes $30 Million Series C Financing

Explosive Growth and Market Leadership Attracts New and Existing Investors

San Carlos, CA – September 22, 2010 – Aster Data, a market leader in big data management and advanced analytics, today announced that it has closed a $30 million Series C round of financing led by both new and existing investors. The company will use the new funding to accelerate growth, scale operations, and expand its global market share in the $20 billion database market – a market that is experiencing rapid growth as a result of both the explosion in data volumes across organizations and the urgent need to deliver a new class of analytics and data-driven applications. The Series C round of funding includes previous investors Sequoia Capital, JAFCO Ventures, Institutional Venture Partners, Cambrian Ventures, as well as an additional new strategic investor.  Also investing in this round is early investor David Cheriton, who previously backed high-growth companies including Google and VMware, and co-founded several successful technology companies.

Today’s Series C funding announcement underscores a year of strong innovation, execution, and overall momentum for the analytic database company. Key milestones include:

Strong sales growth: Since 2008, Aster Data has doubled revenue year-over-year and secured key customers that leverage Aster Data’s platform to address the big data management problem including MySpace, comScore, Barnes & Noble, and Akamai. Like so many organizations today,
Aster Data’s customers are experiencing explosive data growth across their organizations and recognize the need for rich, advanced analytics that give them deeper insights from their data.

Key executive hires: Quentin Gallivan, former CEO of both PivotLink and Postini and EVP of worldwide sales at Verisign, recently joined the company as Chief Executive Officer. In addition, earlier this year, John Calonico, previously at Interwoven, BEA, and Autodesk, joined as Chief Financial Officer; and Nitin Donde, formerly an executive at EMC and 3PAR, joined as Executive Vice President Engineering.  The strength and experience of Aster Data’s management team helps further establish a strong operational foundation for growth in 2010 and beyond.

Industry recognition: Aster Data was positioned in the “Visionaries” Quadrant of Gartner, Inc.’s

Data Warehouse Database Management Systems Magic Quadrant, published 2010 *; was recently named 2011 Tech Pioneer by the World Economic Forum; was named “Company to Watch” in the Information Management category of TechWeb’s Intelligent Enterprise 2010 Editors’ Choice Awards; and was awarded the 2010 San Francisco Business Times Technology and Innovation Award in the Best Product and Services Category.

Product Innovation: Aster Data continues to deliver ground-breaking capabilities to address the big data management and advanced analytics market need. Its recent announcement of
Aster Data nCluster 4.6 includes a column data store, making it the first hybrid row and column MPP DBMS with a unified SQL and MapReduce analytic framework for advanced analytics on large data sets. This year, Aster Data also delivered the most extensive library of pre-packaged MapReduce analytics totaling over 1000 functions, to ease and accelerate delivery of highly advanced analytic applications.

Aster Data’s analytic database, also called a ‘Data-Analytics Server’ is specifically designed to enable organizations to cost effectively store and analyze massive volumes of data. Aster Data leverages the power of commodity, general-purpose hardware, to reduce the cost to scale to support large data volumes and uniquely allows analysis of all data ‘in-database’ enabling richer and faster processing of large data sets. Aster Data’s in-database analytics engine uses the power of MapReduce, a parallel processing framework created by Google.

”The funding we received in our Series C round is a strong endorsement of Aster Data’s market leadership position and the high growth potential of the big data market,” said Quentin Gallivan, Chief Executive Officer, Aster Data. “The Aster Data team has executed exceptionally well to-date and I am excited to have the resources to accelerate the growth of the company as we expand our operations and execute aggressively across all fronts.”