Tag: Analytics

IBM and Revolution team to create new in-database R

From the Press Release at http://www.revolutionanalytics.com/news-events/news-room/2011/revolution-analytics-netezza-partnership.php

Under the terms of the agreement, the companies will work together to create a version of Revolution’s software that takes advantage of IBM Netezza’s i-class technology so that Revolution R Enterprise can run in-database in an optimal fashion.

About IBM

For information about IBM Netezza, please visit: http://www.netezza.com.
For Information on IBM Information Management, please visit: http://www.ibm.com/software/data/information-on-demand/
For information on IBM Business Analytics, please visit the online press kit: http://www.ibm.com/press/us/en/presskit/27163.wss
Follow IBM and Analytics on Twitter: http://twitter.com/ibmbizanalytics
Follow IBM analytics on Tumblr: http://smarterplanet.tumblr.com/tagged/new_intelligence
IBM YouTube Analytics Channel: http://www.youtube.com/user/ibmbusinessanalytics
For information on IBM Smarter Systems: http://www-03.ibm.com/systems/smarter/

About Revolution Analytics

Revolution Analytics is the leading commercial provider of software and services based on the open source R project for statistical computing.  Led by predictive analytics pioneer Norman Nie, the company brings high performance, productivity and enterprise readiness to R, the most powerful statistics language in the world. The company’s flagship Revolution R product is designed to meet the production needs of large organizations in industries such as finance, life sciences, retail, manufacturing and media.  Used by over 2 million analysts in academia and at cutting-edge companies such as Google, Bank of America and Acxiom, R has emerged as the standard of innovation in statistical analysis. Revolution Analytics is committed to fostering the continued growth of the R community through sponsorship of the Inside-R.org community site, funding worldwide R user groups and offers free licenses of Revolution R Enterprise to everyone in academia.


Netezza, an IBM Company, is the global leader in data warehouse, analytic and monitoring appliances that dramatically simplify high-performance analytics across an extended enterprise. IBM Netezza’s technology enables organizations to process enormous amounts of captured data at exceptional speed, providing a significant competitive and operational advantage in today’s data-intensive industries, including digital media, energy, financial services, government, health and life sciences, retail and telecommunications.

The IBM Netezza TwinFin® appliance is built specifically to analyze petabytes of detailed data significantly faster than existing data warehouse options, and at a much lower total cost of ownership. It stores, filters and processes terabytes of records within a single unit, analyzing only the relevant information for each query.

Using Revolution R Enterprise & Netezza Together

Revolution Analytics and IBM Netezza have announced a partnership to integrate Revolution R Enterprise and the IBM Netezza TwinFin  Data Warehouse Appliance. For the first time, customers seeking to run high performance and full-scale predictive analytics from within a data warehouse platform will be able to directly leverage the power of the open source R statistics language. The companies are working together to create a version of Revolution’s software that takes advantage of IBM Netezza’s i-class technology so that Revolution R Enterprise can run in-database in an optimal fashion.

This partnership integrates Revolution R Enterprise with IBM Netezza’s high performance data warehouse and advanced analytics platform to help organizations combat the challenges that arise as complexity and the scale of data grow.  By moving the analytics processing next to the data, this integration will minimize data movement – a significant bottleneck, especially when dealing with “Big Data”.  It will deliver high performance on large scale data, while leveraging the latest innovations in analytics.

With Revolution R Enterprise for IBM Netezza, advanced R computations are available for rapid analysis of hundreds of terabyte-class data volumes — and can deliver 10-100x performance improvements at a fraction of the cost compared to traditional analytics vendors.

Additional Resources


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HIGHLIGHTS from REXER Survey :R gives best satisfaction

Simple graph showing hierarchical clustering. ...
Image via Wikipedia

A Summary report from Rexer Analytics Annual Survey

 

HIGHLIGHTS from the 4th Annual Data Miner Survey (2010):

 

•   FIELDS & GOALS: Data miners work in a diverse set of fields.  CRM / Marketing has been the #1 field in each of the past four years.  Fittingly, “improving the understanding of customers”, “retaining customers” and other CRM goals are also the goals identified by the most data miners surveyed.

 

•   ALGORITHMS: Decision trees, regression, and cluster analysis continue to form a triad of core algorithms for most data miners.  However, a wide variety of algorithms are being used.  This year, for the first time, the survey asked about Ensemble Models, and 22% of data miners report using them.
A third of data miners currently use text mining and another third plan to in the future.

 

•   MODELS: About one-third of data miners typically build final models with 10 or fewer variables, while about 28% generally construct models with more than 45 variables.

 

•   TOOLS: After a steady rise across the past few years, the open source data mining software R overtook other tools to become the tool used by more data miners (43%) than any other.  STATISTICA, which has also been climbing in the rankings, is selected as the primary data mining tool by the most data miners (18%).  Data miners report using an average of 4.6 software tools overall.  STATISTICA, IBM SPSS Modeler, and R received the strongest satisfaction ratings in both 2010 and 2009.

 

•   TECHNOLOGY: Data Mining most often occurs on a desktop or laptop computer, and frequently the data is stored locally.  Model scoring typically happens using the same software used to develop models.  STATISTICA users are more likely than other tool users to deploy models using PMML.

 

•   CHALLENGES: As in previous years, dirty data, explaining data mining to others, and difficult access to data are the top challenges data miners face.  This year data miners also shared best practices for overcoming these challenges.  The best practices are available online.

 

•   FUTURE: Data miners are optimistic about continued growth in the number of projects they will be conducting, and growth in data mining adoption is the number one “future trend” identified.  There is room to improve:  only 13% of data miners rate their company’s analytic capabilities as “excellent” and only 8% rate their data quality as “very strong”.

 

Please contact us if you have any questions about the attached report or this annual research program.  The 5th Annual Data Miner Survey will be launching next month.  We will email you an invitation to participate.

 

Information about Rexer Analytics is available at www.RexerAnalytics.com. Rexer Analytics continues their impressive journey see http://www.rexeranalytics.com/Clients.html

|My only thought- since most data miners are using multiple tools including free tools as well as paid software, Perhaps a pie chart of market share by revenue and volume would be handy.

Also some ideas on comparing diverse data mining projects by data size, or complexity.

 

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Protected: Whats behind that pretty SAS Blog?

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Zementis partners with R Analytics Vendor- Revo

Logo for R
Image via Wikipedia

Just got a  PR email from Michael Zeller,CEO , Zementis annoucing Zementis (ADAPA) and Revolution  Analytics just partnered up.

Is this something substantial or just time-sharing http://bi.cbronline.com/news/sas-ceo-says-cep-open-source-and-cloud-bi-have-limited-appeal or a Barney Partnership (http://www.dbms2.com/2008/05/08/database-blades-are-not-what-they-used-to-be/)

Summary- Thats cloud computing scoring of models on EC2 (Zementis) partnering with the actual modeling software in R (Revolution Analytics RevoDeployR)

See previous interviews with both Dr Zeller at https://decisionstats.com/2009/02/03/interview-michael-zeller-ceozementis/ ,https://decisionstats.com/2009/05/07/interview-ron-ramos-zementis/ and https://decisionstats.com/2009/10/05/interview-michael-zellerceo-zementis-on-pmml/)

and Revolution guys at https://decisionstats.com/2010/08/03/q-a-with-david-smith-revolution-analytics/

and https://decisionstats.com/2009/05/29/interview-david-smith-revolution-computing/

–

strategic partnership with Revolution Analytics, the leading commercial provider of software and support for the popular open source R statistics language. With this partnership, predictive models developed on Revolution R Enterprise are now accessible for real-time scoring through the ADAPA Decisioning Engine by Zementis. 

ADAPA is an extremely fast and scalable predictive platform. Models deployed in ADAPA are automatically available for execution in real-time and batch-mode as Web Services. ADAPA allows Revolution R Enterprise to leverage the Predictive Model Markup Language (PMML) for better decision management. With PMML, models built in R can be used in a wide variety of real-world scenarios without requiring laborious or expensive proprietary processes to convert them into applications capable of running on an execution system.

partnership

“By partnering with Zementis, Revolution Analytics is building an end-to-end solution for moving enterprise-level predictive R models into the execution environment,” said Jeff Erhardt, Revolution Analytics Chief Operation Officer. “With Zementis, we are eliminating the need to take R applications apart and recode, retest and redeploy them in order to obtain desirable results.”
 

Got demo? 

Yes, we do! Revolution Analytics and Zementis have put together a demo which combines the building of models in R with automatic deployment and execution in ADAPA. It uses Revolution Analytics’ RevoDeployR, a new Web Services framework that allows for data analysts working in R to publish R scripts to a server-based installation of Revolution R Enterprise.

Action Items:

  1. Try our INTERACTIVE DEMO
  2. DOWNLOAD the white paper
  3. Try the ADAPA FREE TRIAL

RevoDeployR & ADAPA allow for real-time analysis and predictions from R to be effectively used by existing Excel spreadsheets, BI dashboards and Web-based applications, all in real-time.

RevoADAPAPredictive analytics with RevoDeployR from Revolution Analytics and ADAPA from Zementis put model building and real-time scoring into a league of their own. Seriously!
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Pentaho and R: working together

open_source_communism
Image by jagelado via Flickr

I interview Pentaho Co-founder here at https://decisionstats.com/2010/11/14/pentaho/

and recently became aware of the R Pentaho integration.

“R” is a popular open source statistical and analytical language that academics and commercial organizations alike have used for years to get maximum insight out of information using advanced analytic techniques. In this twelve-minute video, David Reinke from Pentaho Certified Partner OpenBI provides an overview of R, as well as a demonstration of integration between R and Pentaho.

http://www.pentaho.com/products/demos/r_project_with_pentaho/

or http://www.pentaho.com/products/demos/showNtell.php

Related-

M.S. in Applied Statistics

http://www.information-management.com/blogs/analytics_business_intelligence_BI_statistics-10019474-1.html

R and BI – Integrating R with Open Source BusinessIntelligence Platforms Pentaho and Jaspersoft

http://www.r-project.org/conferences/useR-2010/abstracts/Reinke+Miller.pdf

Web development with R

http://www.r-project.org/conferences/useR-2010/slides/Ooms.pdf

In-database analytics with R

http://www.r-project.org/conferences/useR-2010/slides/Hess+Chambers_1.pdf

R role in Business Intelligence Software Architecture

http://www.r-project.org/conferences/useR-2010/slides/Colombo+Ronzoni+Fontana.pdf

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Interview Anne Milley JMP

Here is an interview with Anne Milley, a notable thought leader in the world of analytics. Anne is now Senior Director, Analytical Strategy in Product Marketing for JMP , the leading data visualization software from the SAS Institute.

Ajay-What do you think are the top 5 unique selling points of JMP compared to other statistical software in its category?

Anne-

JMP combines incredible analytic depth and breadth with interactive data visualization, creating a unique environment optimized for discovery and data-driven innovation.

With an extensible framework using JSL (JMP Scripting Language), and integration with SAS, R, and Excel, JMP becomes your analytic hub.

JMP is accessible to all kinds of users. A novice analyst can dig into an interactive report delivered by a custom JMP application. An engineer looking at his own data can use built-in JMP capabilities to discover patterns, and a developer can write code to extend JMP for herself or others.

State-of-the-art DOE capabilities make it easy for anyone to design and analyze efficient experiments to determine which adjustments will yield the greatest gains in quality or process improvement – before costly changes are made.

Not to mention, JMP products are exceptionally well designed and easy to use. See for yourself and check out the free trial at www.jmp.com.

Download a free 30-day trial of JMP.

Ajay- What are the challenges and opportunities of expanding JMP’s market share? Do you see JMP expanding its conferences globally to engage global audiences?

Anne-

We realized solid global growth in 2010. The release of JMP Pro and JMP Clinical last year along with continuing enhancements to the rest of the JMP family of products (JMP and JMP Genomics) should position us well for another good year.

With the growing interest in analytics as a means to sustained value creation, we have the opportunity to help people along their analytic journey – to get started, take the next step, or adopt new paradigms speeding their time to value. The challenge is doing that as fast as we would like.

We are hiring internationally to offer even more events, training and academic programs globally.

Ajay- What are the current and proposed educational and global academic initiatives of JMP? How can we see more JMP in universities across the world (say India- China etc)?

Anne-

We view colleges and universities both as critical incubators of future JMP users and as places where attitudes about data analysis and statistics are formed. We believe that a positive experience in learning statistics makes a person more likely to eventually want and need a product like JMP.

For most students – and particularly for those in applied disciplines of business, engineering and the sciences – the ability to make a statistics course relevant to their primary area of study fosters a positive experience. Fortunately, there is a trend in statistical education toward a more applied, data-driven approach, and JMP provides a very natural environment for both students and researchers.

Its user-friendly navigation, emphasis on data visualization and easy access to the analytics behind the graphics make JMP a compelling alternative to some of our more traditional competitors.

We’ve seen strong growth in the education markets in the last few years, and JMP is now used in nearly half of the top 200 universities in the US.

Internationally, we are at an earlier stage of market development, but we are currently working with both JMP and SAS country offices and their local academic programs to promote JMP. For example, we are working with members of the JMP China office and faculty at several universities in China to support the use of JMP in the development of a master’s curriculum in Applied Statistics there, touched on in this AMSTAT News article.

Ajay- What future trends do you see for 2011 in this market (say top 5)?

Anne-

Growing complexity of data (text, image, audio…) drives the need for more and better visualization and analysis capabilities to make sense of it all.

More “chief analytics officers” are making better use of analytic talent – people are the most important ingredient for success!

JMP has been on the vanguard of 64-bit development, and users are now catching up with us as 64-bit machines become more common.

Users should demand easy-to-use, exploratory and predictive modeling tools as well as robust tools to experiment and learn to help them make the best decisions on an ongoing basis.

All these factors and more fuel the need for the integration of flexible, extensible tools with popular analytic platforms.

Ajay-You enjoy organic gardening as a hobby. How do you think hobbies and unwind time help people be better professionals?

Anne-

I am lucky to work with so many people who view their work as a hobby. They have other interests too, though, some of which are work-related (statistics is relevant everywhere!). Organic gardening helps me put things in perspective and be present in the moment. More than work defines who you are. You can be passionate about your work as well as passionate about other things. I think it’s important to spend some leisure time in ways that bring you joy and contribute to your overall wellbeing and outlook.

Btw, nice interviews over the past several months—I hadn’t kept up, but will check it out more often!

Biography–  Source- http://www.sas.com/knowledge-exchange/business-analytics/biographies.html

  • Anne Milley

    Anne Milley

    Anne Milley is Senior Director of Analytics Strategy at JMP Product Marketing at SAS. Her ties to SAS began with bank failure prediction at Federal Home Loan Bank Dallas and continued at 7-Eleven Inc. She has authored papers and served on committees for F2006, KDD, SIAM, A2010 and several years of SAS’ annual data mining conference. Milley is a contributing faculty member for the International Institute of Analytics. anne.milley@jmp.com

WPS Version 2.5.1 Released – can still run SAS language/data and R

However this is what Phil Rack the reseller is quoting on http://www.minequest.com/Pricing.html

Windows Desktop Price: $884 on 32-bit Windows and $1,149 on 64-bit Windows.

The Bridge to R is available on the Windows platforms and is available for free to customers who
license WPS through MineQuest,LLC. Companies and organizations outside of North America
may purchase a license for the Bridge to R which starts at $199 per desktop or $599 per server

Windows Server Price: $1,903 per logical CPU for 32-bit and $2,474 for 64-bit.

Note that Linux server versions are available but do not yet support the Eclipse IDE and are
command line only

WPS sure seems going well-but their pricing is no longer fixed and on the home website, you gotta fill a form. Ditt0 for the 30 day free evaluation

http://www.teamwpc.co.uk/products/wps/modules/core

Data File Formats

The table below provides a summary of data formats presently supported by the WPS Core module.

Data File Format Un-Compressed
Data		 Compressed
Data
Read Write Read Write
SD2 (SAS version 6 data set)
SAS7BDAT (SAS version 7 data set)
SAS7BDAT (SAS version 8 data set)
SAS7BDAT (SAS version 9 data set)
SASSEQ (SAS version 8/9 sequential file)
V8SEQ (SAS version 8 sequential file)
V9SEQ (SAS version 9 sequential file)
WPD (WPS native data set)
WPDSEQ (WPS native sequential file)
XPORT (transport format)

Additional access to EXCEL, SPSS and dBASE files is supported by utilising the WPS Engine for DB Filesmodule.

and they have a new product release on Valentine Day 2011 (oh these Europeans!)

From the press release at http://www.teamwpc.co.uk/press/wps2_5_1_released

WPS Version 2.5.1 Released 

New language support, new data engines, larger datasets, improved scalability

LONDON, UK – 14 February 2011 – World Programming today released version 2.5.1 of their WPS software for workstations, servers and mainframes.

WPS is a competitively priced, high performance, highly scalable data processing and analytics software product that allows users to execute programs written in the language of SAS. WPS is supported on a wide variety of hardware and operating system platforms and can connect to and work with many types of data with ease. The WPS user interface (Workbench) is frequently praised for its ease of use and flexibility, with the option to include numerous third-party extensions.

This latest version of the software has the ability to manipulate even greater volumes of data, removing the previous 2^31 (2 billion) limit on number of observations.

Complimenting extended data processing capabilities, World Programming has worked hard to boost the performance, scalability and reliability of the WPS software to give users the confidence they need to run heavy workloads whilst delivering maximum value from available computer power.

WPS version 2.5.1 offers additional flexibility with the release of two new data engines for accessing Greenplum and SAND databases. WPS now comes with eleven data engines and can access a huge range of commonly used and industry-standard file-formats and databases.

Support in WPS for the language of SAS continues to expand with more statistical procedures, data step functions, graphing controls and many other language items and options.

WPS version 2.5.1 is available as a free upgrade to all licensed users of WPS.

Summary of Main New Features:

  • Supporting Even Larger Datasets
    WPS is now able to process very large data sets by lifting completely the previous size limit of 2^31 observations.
  • Performance and Scalability Boosted
    Performance and scalability improvements across the board combine to ensure even the most demanding large and concurrent workloads are processed efficiently and reliably.
  • More Language Support
    WPS 2.5.1 continues the expansion of it’s language support with over 70 new language items, including new Procedures, Data Step functions and many other language items and options.
  • Statistical Analysis
    The procedure support in WPS Statistics has been expanded to include PROC CLUSTER and PROC TREE.
  • Graphical Output
    The graphical output from WPS Graphing has been expanded to accommodate more configurable graphics.
  • Hash Tables
    Support is now provided for hash tables.
  • Greenplum®
    A new WPS Engine for Greenplum provides dedicated support for accessing the Greenplum database.
  • SAND®
    A new WPS Engine for SAND provides dedicated support for accessing the SAND database.
  • Oracle®
    Bulk loading support now available in the WPS Engine for Oracle.
  • SQL Server®
    To enhance existing SQL Server database access, a new SQLSERVR (please note spelling) facility in the ODBC engine.

More Information:

Existing Users should visit www.teamwpc.co.uk/support/wps/release where you can download a readme file containing more information about all the new features and fixes in WPS 2.5.1.

New Users should visit www.teamwpc.co.uk/products/wps where you can explore in more detail all the features available in WPS or request a free evaluation.

and from http://www.teamwpc.co.uk/products/wps/data it seems they are going on the BIG DATA submarine as well-

Data Support 

Extremely Large Data Size Handling

WPS is now able to handle extremely large data sets now that the previous limit of 2^31 observations has been lifted.

Access Standard Databases

Use I/O Features in WPS Core

  • CLIPBOARD (Windows only)
  • DDE (Windows only)
  • EMAIL (via SMTP or MAPI)
  • FTP
  • HTTP
  • PIPE (Windows and UNIX only)
  • SOCKET
  • STDIO
  • URL

Use Standard Data File Formats

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