Churn Analytics Contest at Crowd Analytix

Crowd Analytix- the Bangalore based Indian startup is moving fast in the

data scientist contest space (so watch out Kaggle!! )


Churn (loss of customers to competition) is a problem for telecom companies because it is more expensive to acquire a new customer than to keep your existing one from leaving. This contest is about enabling churn reduction using analytics.

To join, go to – http://www.crowdanalytix.com/contests/why-customer-churn/

Oracle launches its version of R #rstats

From-

http://www.oracle.com/us/corporate/press/1515738

Integrates R Statistical Programming Language into Oracle Database 11g

News Facts

Oracle today announced the availability of Oracle Advanced Analytics, a new option for Oracle Database 11g that bundles Oracle R Enterprise together with Oracle Data Mining.
Oracle R Enterprise delivers enterprise class performance for users of the R statistical programming language, increasing the scale of data that can be analyzed by orders of magnitude using Oracle Database 11g.
R has attracted over two million users since its introduction in 1995, and Oracle R Enterprise dramatically advances capability for R users. Their existing R development skills, tools, and scripts can now also run transparently, and scale against data stored in Oracle Database 11g.
Customer testing of Oracle R Enterprise for Big Data analytics on Oracle Exadata has shown up to 100x increase in performance in comparison to their current environment.
Oracle Data Mining, now part of Oracle Advanced Analytics, helps enable customers to easily build and deploy predictive analytic applications that help deliver new insights into business performance.
Oracle Advanced Analytics, in conjunction with Oracle Big Data ApplianceOracle Exadata Database Machine and Oracle Exalytics In-Memory Machine, delivers the industry’s most integrated and comprehensive platform for Big Data analytics.

Comprehensive In-Database Platform for Advanced Analytics

Oracle Advanced Analytics brings analytic algorithms to data stored in Oracle Database 11g and Oracle Exadata as opposed to the traditional approach of extracting data to laptops or specialized servers.
With Oracle Advanced Analytics, customers have a comprehensive platform for real-time analytic applications that deliver insight into key business subjects such as churn prediction, product recommendations, and fraud alerting.
By providing direct and controlled access to data stored in Oracle Database 11g, customers can accelerate data analyst productivity while maintaining data security throughout the enterprise.
Powered by decades of Oracle Database innovation, Oracle R Enterprise helps enable analysts to run a variety of sophisticated numerical techniques on billion row data sets in a matter of seconds making iterative, speed of thought, and high-quality numerical analysis on Big Data practical.
Oracle R Enterprise drastically reduces the time to deploy models by eliminating the need to translate the models to other languages before they can be deployed in production.
Oracle R Enterprise integrates the extensive set of Oracle Database data mining algorithms, analytics, and access to Oracle OLAP cubes into the R language for transparent use by R users.
Oracle Data Mining provides an extensive set of in-database data mining algorithms that solve a wide range of business problems. These predictive models can be deployed in Oracle Database 11g and use Oracle Exadata Smart Scan to rapidly score huge volumes of data.
The tight integration between R, Oracle Database 11g, and Hadoop enables R users to write one R script that can run in three different environments: a laptop running open source R, Hadoop running with Oracle Big Data Connectors, and Oracle Database 11g.
Oracle provides single vendor support for the entire Big Data platform spanning the hardware stack, operating system, open source R, Oracle R Enterprise and Oracle Database 11g.
To enable easy enterprise-wide Big Data analysis, results from Oracle Advanced Analytics can be viewed from Oracle Business Intelligence Foundation Suite and Oracle Exalytics In-Memory Machine.

Supporting Quotes

“Oracle is committed to meeting the challenges of Big Data analytics. By building upon the analytical depth of Oracle SQL, Oracle Data Mining and the R environment, Oracle is delivering a scalable and secure Big Data platform to help our customers solve the toughest analytics problems,” said Andrew Mendelsohn, senior vice president, Oracle Server Technologies.
“We work with leading edge customers who rely on us to deliver better BI from their Oracle Databases. The new Oracle R Enterprise functionality allows us to perform deep analytics on Big Data stored in Oracle Databases. By leveraging R and its library of open source contributed CRAN packages combined with the power and scalability of Oracle Database 11g, we can now do that,” said Mark Rittman, co-founder, Rittman Mead.
Oracle Advanced Analytics — an option to Oracle Database 11g Enterprise Edition – extends the database into a comprehensive advanced analytics platform through two major components: Oracle R Enterprise and Oracle Data Mining. With Oracle Advanced Analytics, customers have a comprehensive platform for real-time analytic applications that deliver insight into key business subjects such as churn prediction, product recommendations, and fraud alerting.

Oracle R Enterprise tightly integrates the open source R programming language with the database to further extend the database with Rs library of statistical functionality, and pushes down computations to the database. Oracle R Enterprise dramatically advances the capability for R users, and allows them to use their existing R development skills and tools, and scripts can now also run transparently and scale against data stored in Oracle Database 11g.

Oracle Data Mining provides powerful data mining algorithms that run as native SQL functions for in-database model building and model deployment. It can be accessed through the SQL Developer extension Oracle Data Miner to build, evaluate, share and deploy predictive analytics methodologies. At the same time the high-performance Oracle-specific data mining algorithms are accessible from R.

BENEFITS

  • Scalability—Allows customers to easily scale analytics as data volume increases by bringing the algorithms to where the data resides – in the database
  • Performance—With analytical operations performed in the database, R users can take advantage of the extreme performance of Oracle Exadata
  • Security—Provides data analysts with direct but controlled access to data in Oracle Database 11g, accelerating data analyst productivity while maintaining data security
  • Save Time and Money—Lowers overall TCO for data analysis by eliminating data movement and shortening the time it takes to transform “raw data” into “actionable information”
Oracle R Hadoop Connector Gives R users high performance native access to Hadoop Distributed File System (HDFS) and MapReduce programming framework.
This is a  R package
From the datasheet at

Awesome Case Study by PayPal/ Rapid Miner for Churn

I just saw this awesome case study of using Rapid Miner for predicting Churn in financial services (Paypal). I had been looking for simple yet exhaustive manuals/case studies on churn modeling and this is one the better ones I have seen. http://rapid-i.com/downloads/press/PayPalCaseStudyChurnRiskDetectionv1.1-web.pdf

 

Interview Dan Steinberg Founder Salford Systems

Here is an interview with Dan Steinberg, Founder and President of Salford Systems (http://www.salford-systems.com/ )

Ajay- Describe your journey from academia to technology entrepreneurship. What are the key milestones or turning points that you remember.

 Dan- When I was in graduate school studying econometrics at Harvard,  a number of distinguished professors at Harvard (and MIT) were actively involved in substantial real world activities.  Professors that I interacted with, or studied with, or whose software I used became involved in the creation of such companies as Sun Microsystems, Data Resources, Inc. or were heavily involved in business consulting through their own companies or other influential consultants.  Some not involved in private sector consulting took on substantial roles in government such as membership on the President’s Council of Economic Advisors. The atmosphere was one that encouraged free movement between academia and the private sector so the idea of forming a consulting and software company was quite natural and did not seem in any way inconsistent with being devoted to the advancement of science.

 Ajay- What are the latest products by Salford Systems? Any future product plans or modification to work on Big Data analytics, mobile computing and cloud computing.

 Dan- Our central set of data mining technologies are CART, MARS, TreeNet, RandomForests, and PRIM, and we have always maintained feature rich logistic regression and linear regression modules. In our latest release scheduled for January 2012 we will be including a new data mining approach to linear and logistic regression allowing for the rapid processing of massive numbers of predictors (e.g., one million columns), with powerful predictor selection and coefficient shrinkage. The new methods allow not only classic techniques such as ridge and lasso regression, but also sub-lasso model sizes. Clear tradeoff diagrams between model complexity (number of predictors) and predictive accuracy allow the modeler to select an ideal balance suitable for their requirements.

The new version of our data mining suite, Salford Predictive Modeler (SPM), also includes two important extensions to the boosted tree technology at the heart of TreeNet.  The first, Importance Sampled learning Ensembles (ISLE), is used for the compression of TreeNet tree ensembles. Starting with, say, a 1,000 tree ensemble, the ISLE compression might well reduce this down to 200 reweighted trees. Such compression will be valuable when models need to be executed in real time. The compression rate is always under the modeler’s control, meaning that if a deployed model may only contain, say, 30 trees, then the compression will deliver an optimal 30-tree weighted ensemble. Needless to say, compression of tree ensembles should be expected to be lossy and how much accuracy is lost when extreme compression is desired will vary from case to case. Prior to ISLE, practitioners have simply truncated the ensemble to the maximum allowable size.  The new methodology will substantially outperform truncation.

The second major advance is RULEFIT, a rule extraction engine that starts with a TreeNet model and decomposes it into the most interesting and predictive rules. RULEFIT is also a tree ensemble post-processor and offers the possibility of improving on the original TreeNet predictive performance. One can think of the rule extraction as an alternative way to explain and interpret an otherwise complex multi-tree model. The rules extracted are similar conceptually to the terminal nodes of a CART tree but the various rules will not refer to mutually exclusive regions of the data.

 Ajay- You have led teams that have won multiple data mining competitions. What are some of your favorite techniques or approaches to a data mining problem.

 Dan- We only enter competitions involving problems for which our technology is suitable, generally, classification and regression. In these areas, we are  partial to TreeNet because it is such a capable and robust learning machine. However, we always find great value in analyzing many aspects of a data set with CART, especially when we require a compact and easy to understand story about the data. CART is exceptionally well suited to the discovery of errors in data, often revealing errors created by the competition organizers themselves. More than once, our reports of data problems have been responsible for the competition organizer’s decision to issue a corrected version of the data and we have been the only group to discover the problem.

In general, tackling a data mining competition is no different than tackling any analytical challenge. You must start with a solid conceptual grasp of the problem and the actual objectives, and the nature and limitations of the data. Following that comes feature extraction, the selection of a modeling strategy (or strategies), and then extensive experimentation to learn what works best.

 Ajay- I know you have created your own software. But are there other software that you use or liked to use?

 Dan- For analytics we frequently test open source software to make sure that our tools will in fact deliver the superior performance we advertise. In general, if a problem clearly requires technology other than that offered by Salford, we advise clients to seek other consultants expert in that other technology.

 Ajay- Your software is installed at 3500 sites including 400 universities as per http://www.salford-systems.com/company/aboutus/index.html What is the key to managing and keeping so many customers happy?

 Dan- First, we have taken great pains to make our software reliable and we make every effort  to avoid problems related to bugs.  Our testing procedures are extensive and we have experts dedicated to stress-testing software . Second, our interface is designed to be natural, intuitive, and easy to use, so the challenges to the new user are minimized. Also, clear documentation, help files, and training videos round out how we allow the user to look after themselves. Should a client need to contact us we try to achieve 24-hour turn around on tech support issues and monitor all tech support activity to ensure timeliness, accuracy, and helpfulness of our responses. WebEx/GotoMeeting and other internet based contact permit real time interaction.

 Ajay- What do you do to relax and unwind?

 Dan- I am in the gym almost every day combining weight and cardio training. No matter how tired I am before the workout I always come out energized so locating a good gym during my extensive travels is a must. I am also actively learning Portuguese so I look to watch a Brazilian TV show or Portuguese dubbed movie when I have time; I almost never watch any form of video unless it is available in Portuguese.

 Biography-

http://www.salford-systems.com/blog/dan-steinberg.html

Dan Steinberg, President and Founder of Salford Systems, is a well-respected member of the statistics and econometrics communities. In 1992, he developed the first PC-based implementation of the original CART procedure, working in concert with Leo Breiman, Richard Olshen, Charles Stone and Jerome Friedman. In addition, he has provided consulting services on a number of biomedical and market research projects, which have sparked further innovations in the CART program and methodology.

Dr. Steinberg received his Ph.D. in Economics from Harvard University, and has given full day presentations on data mining for the American Marketing Association, the Direct Marketing Association and the American Statistical Association. After earning a PhD in Econometrics at Harvard Steinberg began his professional career as a Member of the Technical Staff at Bell Labs, Murray Hill, and then as Assistant Professor of Economics at the University of California, San Diego. A book he co-authored on Classification and Regression Trees was awarded the 1999 Nikkei Quality Control Literature Prize in Japan for excellence in statistical literature promoting the improvement of industrial quality control and management.

His consulting experience at Salford Systems has included complex modeling projects for major banks worldwide, including Citibank, Chase, American Express, Credit Suisse, and has included projects in Europe, Australia, New Zealand, Malaysia, Korea, Japan and Brazil. Steinberg led the teams that won first place awards in the KDDCup 2000, and the 2002 Duke/TeraData Churn modeling competition, and the teams that won awards in the PAKDD competitions of 2006 and 2007. He has published papers in economics, econometrics, computer science journals, and contributes actively to the ongoing research and development at Salford.

Text Analytics World in New York

There is a 15 % discount if you want to register for Text Analytics World next month-

Use Discount Code AJAYNY11

October 19-20, 2011 at The Hilton New York

http://www.textanalyticsworld.com/newyork/2011

Text Analytics World Topics & Case Studies - Oct 19-20 in NYC

Text Analytics World NYC (tawgo.com) is the business-focused event for text analytics professionals,
managers and commercial practitioners. This conference delivers case studies, expertise and resources
to leverage unstructured data for business impact.
Text Analytics World NYC is packed with the top predictive analytics experts, practitioners, authors and
business thought leaders, including keynote addresses from Thomas Davenport, author of Competing
on Analytics: The New Science of Winning, David Gondek from IBM Research on their Jeopardy-Winning
Watson and DeepQA, and PAW Program Chair Eric Siegel, plus special sessions from industry heavy-
weights Usama Fayyad and John Elder.
CASE STUDIES:

TAW New York City will feature over 25 sessions with case studies from leading enterprises in
automotive, educational, e-commerce, financial services, government, high technology, insurance,
retail, social media, and telecom such as: Accident Fund, Amdocs, Bundle.com, Citibank, Florida State
College, Google, Intuit, MetLife, Mitchell1, PayPal, Snap-on, Socialmediatoday, Topsy, a Fortune 500
global technology company, plus special examples from U.S. government agencies DoD, DHS, and SSA.

HOT TOPICS:

TAW New York City's agenda covers hot topics and advanced methods such as churn risk detection,
customer service and call centers, decision support, document discovery, document filtering, financial
indicators from social media, fraud detection, government applications, insurance applications,
knowledge discovery, open question-answering, parallelized text analysis, risk profiling, sentiment
analysis, social media applications, survey analysis, topic discovery, and voice of the customer and other
innovative applications that benefit organizations in new and creative ways.

WORKSHOPS: TAW also features a full-day, hands-on text analytics workshop, plus several other pre-
and post-conference workshops in analytics that complement the core conference program. For more
info: www.tawgo.com/newyork/2011/analytics-workshops
For more information: tawgo.com
Download the conference preview:
Conference Preview for TAW New York, October 19-20 2011
View the agenda at-a-glance: textanalyticsworld.com/newyork/2011/agenda Register by September 2nd for Early Bird Rates (save up to $200): textanalyticsworld.com/newyork/2011/registration If you'd like our informative event updates, sign up at: http://www.textanalyticsworld.com/subscription.php To sign up for TAW group on LinkedIn: www.linkedin.com/e/gis/3869759 For inquiries e-mail regsupport@risingmedia.com or call (717) 798-3495. OTHER ANALYTICS EVENTS: Predictive Analytics World for Government: Sept 12-13 in DC – www.pawgov.com Predictive Analytics World New York City: Oct 16-21 – www.pawcon.com/nyc Text Analytics World New York City: Oct 19-20 – www.tawgo.com/nyc Predictive Analytics World London: Nov 30-Dec 1 – www.pawcon.com/london Predictive Analytics World San Francisco: March 4-10, 2012 – www.pawcon.com/sanfrancisco Predictive Analytics World Videos: Available on-demand – www.pawcon.com/video
Also has two sessions on R

Sunday, October 16, 2011


Half-day Workshop
Room: Madison

R Bootcamp
Click here for the detailed workshop description

  • Workshop starts at 1:00pm
  • Afternoon Coffee Break at 2:30pm – 3:00pm
  • End of the Workshop: 5:00pm

Instructor: Max Kuhn, Director, Nonclinical Statistics, Pfizer

Top of this page ] [ Agenda overview ]

Monday, October 17, 2011


Full-day Workshop
Room: Madison

R for Predictive Modeling: A Hands-On Introduction
Click here for the detailed workshop description

  • Workshop starts at 9:00am
  • Morning Coffee Break at 10:30am – 11:00am
  • Lunch provided at 12:30 – 1:15pm
  • Afternoon Coffee Break at 2:30pm – 3:00pm
  • End of the Workshop: 4:30pm

Instructor: Max Kuhn, Director, Nonclinical Statistics, Pfizer

Analytics 2011 Conference

From http://www.sas.com/events/analytics/us/

The Analytics 2011 Conference Series combines the power of SAS’s M2010 Data Mining Conference and F2010 Business Forecasting Conference into one conference covering the latest trends and techniques in the field of analytics. Analytics 2011 Conference Series brings the brightest minds in the field of analytics together with hundreds of analytics practitioners. Join us as these leading conferences change names and locations. At Analytics 2011, you’ll learn through a series of case studies, technical presentations and hands-on training. If you are in the field of analytics, this is one conference you can’t afford to miss.

Conference Details

October 24-25, 2011
Grande Lakes Resort
Orlando, FL

Analytics 2011 topic areas include:

Predictive Analytics World

Here is an announcement from Predictive Analytics World, the worlds largest vendor neutral conference dedicated to Predictive Analytics alone. Decisionstats has been a blog partner of PAWCON since inception. This is cool stuff!Predictive Analytics World New York October 2011

Video Testimonials: Reasons to Attend Predictive Analytics World Oct 2011, NY  

What’s Predictive Analytics World (PAW) all about and why should you go? See and hear experiences from those who have attended PAW. The video recorded at PAW San Francisco 2011 includes statements from Thomas Davenport, conference chair Eric Siegel, and other conference participants and VIPs.

 

Join your peers October 17-21, 2011 at the Hilton New York for Predictive Analytics World, the business event for predictive analytics professionals, managers and commercial practitioners, covering today’s commercial deployment of predictive analytics, across industries and across software vendors.

Register using the code REDC before June 15th and 10% of your registration proceeds will be donated to American Red Cross Midwest Tornado Relief Effort. Also, take advantage of Super Early Bird Pricing and realize $400 in savings.

Discover new content covering all the latest topics and advanced methods by participating in PAW’s workshops, case studies, and educational sessions.   View full agenda and topics online now.

PAW NYC agenda highlights include:

  • Keynotes from Tom Davenport, President’s Distinguished Professor, Babson College, Author, Competing on Analytics and Eric Siegel,  Conference Program Chair, Predictive Analytics World
  • Special plenary sessions from industry heavyweights, Usama Fayyad, Ph.D., CEO, Open Insights and John F. Elder, CEO and Founder, Elder Research
  • Full day workshops that cover the topics of Decisioning, Core Methods, Net Lift Modeling, Hands-On Intro, Hands-On R, Intro to Predictive Analytics and Intro to Business Analytics
  • Topics covering black box trading, churn modeling, crowdsourcing, demand forecasting, ensemble models, fraud detection, healthcare, insurance applications, law enforcement, litigation, market mix modeling, mobile analytics, online marketing, risk management, social data, supply chain management, targeting direct marketing, uplift modeling (net lift), and other innovative applications that benefit organizations in new and creative ways.
Thomas Davenport
Thomas Davenport
Author, Competing on Analytics
Eric Siegel, Ph.D
VIP from IBM Research (TBA)
Keynote on Jeopardy-Winning Watson and DeepQA
Eric Siegel, Ph.D
Eric Siegel, Ph.D
Program Chair, Predictive Analytics World
Usama Fayyad, Ph.D
Usama Fayyad, Ph.D
CEO, Open Insights
John F. Elder IV, Ph.D
John F. Elder IV, Ph.D
Chief Scientist, Elder Research, Inc.

Become an invaluable resource to your organization by discovering new processes and tactics that your peers are using to optimize with the best methods that leverage data – bringing their business results to the next level.

New Financial Services Track — You Asked and We Delivered

October’s event will include a new conference track of sessions dedicated to the Financial Services industry. This track will feature something for users of all levels, whether you’re deploying your first initiative or learning new ways to position analytics within your organization.


Text analytics. The new conference Text Analytics World,
co-located with PAW NYC, complements PAW’s agenda
with reasonable cross-registration options.

Take advantage of Super Early Bird Pricing and realize
$400 in savings before June 15, 2011.

Note:  Each additional attendee from the same company registered at the same time receives an extra $200 off the Conference Pass.

Register Now!


eMetrics New York

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All Analytics Conferences: 

Predictive Analytics World for Government – Sept 12-13 in DC
Predictive Analytics World NYC – Oct 17-21
Text Analytics World NYC – Oct 19-20
Predictive Analytics World San Francisco – March 2012
Predictive Analytics World Videos – Available on-demand

Produced by: 

Predictionimpact
RisingMedia