PAW Blog Partner and 15 % off for you

paw09_blog_125

Dear Readers,

If you plan to attend Predictive Analytics World ( Oct20-21) in Washington DC,

Here are the speakers – source

Speakers Washington DC 2009:

Stephen L. Baker, Senior writer, BusinessWeek

Stephen L. BakerStephen L. Baker, author of The Numerati, is a senior writer at BusinessWeek, covering technology. Previously he was a Paris correspondent. Baker joined BusinessWeek in March, 1987, as manager of the Mexico City bureau, where he was responsible for covering Mexico and Latin America. He was named Pittsburgh bureau manager in 1992. Before BusinessWeek, Baker was a reporter for the El Paso Herald-Post. Prior to that, he was chief economic reporter for The Daily Journal in Caracas, Venezuela. Baker holds a bachelor’s degree from the University of Wisconsin and a master’s from the Columbia University Graduate School of Journalism. He blogs at TheNumerati.net and Blogspotting.net, and can be found on Twitter at @stevebaker.


John F. Elder, Ph.D., CEO and Founder, Elder Research, Inc.

Dr. John F. ElderDr. John F. Elder heads a data mining consulting team with offices in Charlottesville, Virginia and Washington DC. Founded in 1995, Elder Research, Inc. focuses on scientific and commercial applications of pattern discovery and optimization, including stock selection, image recognition, text mining, biometrics, drug efficacy, credit scoring, cross-selling, investment timing, and fraud detection.

John obtained a BS and MEE in Electrical Engineering from Rice University, and a PhD in Systems Engineering from the University of Virginia, where he’s an adjunct professor, teaching Optimization or Data Mining. Prior to 13 years leading ERI, he spent 5 years in aerospace defense consulting, 4 heading research at an investment management firm, and 2 in Rice’s Computational & Applied Mathematics department.

Dr. Elder has authored innovative data mining tools, is active on Statistics, Engineering, and Finance conferences and boards, is a frequent keynote conference speaker, and is General Chair of the 2009 Knowledge Discovery and Data Mining conference in Paris. John’s courses on data analysis techniques – taught at dozens of universities, companies, and government labs – are noted for their clarity and effectiveness. Dr. Elder was honored to serve for 5 years on a panel appointed by the President to guide technology for National Security. His book on Practical Data Mining, with Bob Nisbet and Gary Minor, will appear in May 2009.


Usama Fayyad, Ph.D., CEO, Open Insights

Dr. Usama FayyadDr. Usama Fayyad was until recently Yahoo!’s Chief Data Officer and Executive Vice President of Research & Strategic Data Solutions where he was responsible for Yahoo!’s global data strategy, architecting Yahoo!’s data policies and systems, prioritizing data investments, and managing the Company’s data analytics and data processing infrastructure. Fayyad also founded and oversaw the Yahoo! Research organization with offices around the world. Yahoo! Research is building the premier scientific research organization to develop the new sciences of the Internet, on-line marketing, and innovative interactive applications.

Prior to joining Yahoo!, Fayyad co-founded and led the DMX Group, a data mining and data strategy consulting and technology company that was acquired by Yahoo! in 2004. In early 2000, he co-founded and served as CEO of Revenue Science, Inc.(digiMine, Inc.), a data analysis and data mining company that built, operated and hosted data warehouses and analytics for some of the world’s largest enterprises in online publishing, retail, manufacturing, telecommunications and financial services. The company today specializes in Behavioral Targeting and advertising networks. Fayyad’s professional experience also includes five years spent leading the data mining and exploration group at Microsoft Research and building the data mining products for Microsoft’s server division. From 1989 to 1996 Fayyad held a leadership role at NASA’s Jet Propulsion Laboratory (JPL), where his work in the analysis and exploration of scientific databases gathered from observatories, remote-sensing platforms and spacecraft garnered him the top research excellence award that Caltech awards to JPL scientists, as well as a U.S. Government medal from NASA.

Fayyad earned his Ph.D. in engineering from the University of Michigan, Ann Arbor (1991), and also holds BSE’s in both electrical and computer engineering (1984); MSE in computer science and engineering (1986); and M.Sc. in mathematics (1989). He has published over 100 technical articles in the fields of data mining and Artificial Intelligence, is a Fellow of the AAAI and a Fellow of the ACM, has edited two influential books on the data mining and launched and served as editor-in-chief of both the primary scientific journal in the field of data mining and the primary newsletter in the technical community published by the ACM: SIGKDD Explorations.


Eric Siegel, Ph.D., Conference Chair

Eric SiegelThe president of Prediction Impact, Inc., Eric Siegel is an expert in predictive analytics and data mining and a former computer science professor at Columbia University, where he won awards for teaching, including graduate-level courses in machine learning and intelligent systems – the academic terms for predictive analytics. After Columbia, Dr. Siegel co-founded two software companies for customer profiling and data mining, and then started Prediction Impact in 2003, providing predictive analytics services and training to mid-tier through Fortune 100 companies.

Dr. Siegel is the instructor of the acclaimed training program, Predictive Analytics for Business, Marketing and Web, and the online version, Predictive Analytics Applied. He has published 13 papers in data mining research and computer science education, has served on 10 conference program committees, and has chaired a AAAI Symposium held at MIT.

you can register at http://www.predictiveanalyticsworld.com/register.php

Here is the pricing

Pricing
Predictive Analytics World Fall 2009

Includes breakfasts, lunches, priceless networking during coffee breaks, the PAW Reception, and full access to program sessions and sponsor expositions.

Super Early Bird Price
(till June 30)
Early Bird Price
(July 1 – Sept 4)
Regular     Price

Two Day Pass
(Oct 20-21)

$1190 $1390 $1590

Predictive Modeling Methods Workshop
(Oct 22)

$695 $795 $895

Putting Predictive Analytics to Work
(Oct 19)

$695 $795 $895

The discount code I can distribute to you  readers is the following: BLOGDC09 (15% off a two-day pass).You can do the maths…

(Ajay- Nopes I dont get money at all in these activities as blasted by some people
- but I do hope to get some good karma. Have a good time and book now).

PAW is back

The Predictive Analytics world is going to be back in October soon , and all those who missed out the stelar event can start booking now.

Here is the official BR ( blog Release)

Source: http://www.predictiveanalyticsworld.com/blog/wp-trackback.php?p=20

June 5th 2009 10:46 am

Keynotes at October’s PAW: Stephen Baker and Usama Fayyad

Predictive Analytics World, coming October 20-21 to Washington DC, has a great line-up of keynote speakers:

Stephen Baker, author of The Numerati and senior writer at BusinessWeek, where he’s been since 1987. Steve’s book has received a tremendous amount of attention this year. It is a revealing and insightful exploration of the opportunities and pitfalls of applied analytics, and consumer perception thereof.

Usama Fayyad, Ph.D. — CEO, Open Insights and formerly Yahoo!’s Chief Data Officer and Executive Vice President of Research & Strategic Data Solutions. Dr. Fayyad will return as an acclaimed keynote speaker. His keynote at February’s PAW (San Francisco) received extremely strong ratings from conference attendees.

Finally, Eric Siegel, Ph.D., will be kicking off PAW with a reprise of his keynote, “Five Ways to Lower Costs with Predictive Analytics.”

PMML 4.0

There are some nice changes in the PMML 4.0 version. PMML is the XML version for data modeling , or specificallyquoting the DMG group itself

PMML uses XML to represent mining models. The structure of the models is described by an XML Schema. One or more mining models can be contained in a PMML document. A PMML document is an XML document with a root element of type PMML. The general structure of a PMML document is:

  <?xml version="1.0"?>
  <PMML version="4.0"
    xmlns="http://www.dmg.org/PMML-4_0"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" >

    <Header copyright="Example.com"/>
    <DataDictionary> ... </DataDictionary>

    ... a model ...

  </PMML>

So what is new in version 4. Here are some powerful modeling changes. For anyone with any XML knowledge PMML is the way to go.

PMML 4.0 – Changes from PMML 3.2

Associations

  • Itemset and AssociationRule elements are no longer enclosed within a “Choice” element
  • Added different scoring procedures: recommendation, exclusiveRecommendation and ruleAssociation with explanation and example
  • Changed version to “4.0” from “3.2” in the example(s)

BuiltinFunctions

Added the following functions:
  • isMissing
  • isNotMissing
  • equal
  • notEqual
  • lessThan
  • lessOrEqual
  • greaterThan
  • greaterOrEqual
  • isIn
  • isNotIn
  • and
  • or
  • not
  • isIn
  • isNotIn
  • if

Click on Image for better resolution

ClusteringModel

  • Changed version to “4.0” from “3.2” in the example(s)
  • Added reference to ModelExplanation element in the model XSD

Conformance

  • Changed all version references from “3.2” to “4.0”

DataDictionary

  • No changes

Functions

  • No changes

GeneralRegression

  • Changed to allow for Cox survival models and model ensembles
    • Add new model type: CoxRegression.
    • Allow empty regression model when model type is CoxRegression, so that baseline-only model could be represented.
    • Add new optional model attributes: endTimeVariable, startTimeVariable, subjectIDVariable, statusVariable, baselineStrataVariable, modelDF.
    • Add optional Matrix in Predictor to specify a contrast matrix, optional attribute referencePoint in Parameter.
    • Add new elements: BaseCumHazardTables, EventValues, BaselineStratum, BaselineCell.
    • Add examples of scoring for Cox Regression and contrast matrices.
    • Add new type of distribution: tweedie.
    • Add new attribute in model: targetReferenceCategory, so that the model can be used in MiningModel.
    • Changed version to “4.0” from “3.2” in the example(s)
    • Added reference to ModelExplanation element in the model XSD

GeneralStructure

Header

  • No changes

Interoperability

  • Changed: “As a result, a new approach for interoperability was required and is being introduced in PMML version 3.2.” to “As a result, a new approach for interoperability was introduced in PMML version 3.2.”

MiningSchema

  • Added frequencyWeight and analysisWeight as new options for usageType. They will not affect scoring, but will make model information more complete.

ModelComposition — No longer used, replaced by MultipleModels

ModelExplanation

  • New addition to PMML 4.0 that contains information to explain the models, model fit statistics, and visualization information.

ModelVerification

  • No changes

MultipleModels

  • Replaces ModelComposition. Important additions are segmentation and ensembles.
  • Added reference to ModelExplanation element in the model XSD

NaïveBayes

  • Changed version to “4.0” from “3.2” in the example(s)
  • Added reference to ModelExplanation element in the model XSD

NeuralNetwork

  • Changed version to “4.0” from “3.2” in the example(s)
  • Added reference to ModelExplanation element in the model XSD

Output

  • Extended output type to include Association rule models. The changes add a number of new attributes: “ruleFeature”, “algorithm”, “rank”, “rankBasis”, “rankOrder” and “isMultiValued”. A new enumeration type “ruleValue” is added to the RESULT-FEATURE

Regression

  • Changed version to “4.0” from “3.2” in the example(s)
  • Added reference to ModelExplanation element in the model XSD

RuleSet

  • Changed version to “4.0” from “3.2” in the example(s)
  • Added reference to ModelExplanation element in the model XSD

Sequence

  • Changed version to “4.0” from “3.2” in the example(s)

Statistics

  • accommodate weighted counts by replacing INT-ARRAY with NUM-ARRAY in DiscrStats and ContStats
  • change xs:nonNegativeInteger to xs:double in several places
  • add new boolean attribute ‘weighted’ to UnivariateStats and PartitionFieldStats elements
  • add new attribute cardinality in Counts
  • Also some very long lines in this document are now wrapped.

SupportVectorMachine

  • Added optional attribute threshold
  • Added optional attribute classificationMethod
  • Attribute alternateTargetCategory removed from SupportVectorMachineModel element and moved to SupportVectorMachine element
  • Changed the example slightly
  • Changed version to “4.0” from “3.2” in the example(s)
  • Added reference to ModelExplanation element in the model XSD

Targets

  • No changes

Taxonomy

  • Changed: “A TableLocator may contain any description which helps an application to locate a certain table. PMML 3.2 does not yet define the content. PMML users have to use their own extensions. The same applies to InlineTable.” to “A TableLocator may contain any description which helps an application to locate a certain table. PMML standard does not yet define the content. PMML users have to use their own extensions. The same applies to InlineTable.”

Text

  • Changed version to “4.0” from “3.2” in the example(s)
  • Added reference to ModelExplanation element in the model XSD

TimeSeriesModel

  • New addition to PMML 4.0 to support Time series models

Transformations

  • No changes

TreeModel

  • Changed version to “4.0” from “3.2” in the example(s)
  • Added reference to ModelExplanation element in the model XSD

Sources

http://www.dmg.org/v4-0/GeneralStructure.html

http://www.dmg.org/v4-0/Changes.html

and here are some companies using PMML already

http://www.dmg.org/products.html

I found the tool at http://www.dmg.org/coverage/ much more interesting though (see screenshot).

Screenshot-Mozilla Firefox

Zementis who we have covered in the interviews has played a steller role in bring together this common standard for data mining. Note Kxen model is also highlighted there.

The best PMML convertor tutorial is here

http://www.zementis.com/videos/PMML_Converter_iGoogle_gadget_2_demo.htm

Teratec : High Performance Computing Event

Here is a good HC event.

The Ter@tec’09 Forum
June 30 and July 1st, 2009, Supélec (91- France)


Incidently it is also quite close to KDD conference http://www.decisionstats.com/2009/06/19/conference-of-the-year-kdd-2009/

High performance Simulation and Computing for competitiveness, innovation and employment

© Ter@tec 2008 CEA

The international HPC event
The  Ter@tec annual Forum, created in 2006, is a major occasion of meetings, exchanges and reflection in the field of high performance simulation and computing.

Since the success of its first edition, the Ter@tec Forum has developed and is now organized on two days with plenary conferences, workshops and exhibition.

In 2008, more than 400 international attendees, from research and industry, providers and users, met to review the largest worldwide programs and discuss the perspectives and the major challenges we are facing, both on the technology side and on the user side.

The Forum was recognized as very successful, with high-level presentations and workshops, and the personal participation of Mrs Valérie Pécresse, French Minister for Higher education and Research and Mr Janez PotoČnik, European Commissioner for Science and Research.

Ter@tec 2009, the meeting of the HPC community around the technological and economical aspects of the high performance simulation and computing development.

Source- http://www.teratec.eu/gb/forum/index.html

Interview Gary Cokins SAS Institute

Here is an interview with Gary Cokins , a well respected veteran of the Business Intelligence industry working with the SAS Institute. Gary has just launched his sixth book (wow!) and the gentlemen he is , he agreed to answer these questions en route to his constant traveling.Gary is the expert on performance measurement so we decided to quiz him a bit on this.

CIO’s need to shift their mindset from a technical one to a managerial one.- Gary Cokins, SAS Institute

Gary_Cokins_SAS_05

Ajay -Gary, please describe your career journey from a freshman in college to your position today. What are the key items of advice that you would give to high school students to encourage taking science careers in this recession?

COKINS: I have been very fortunate. After receiving my MBA in 1974 from the Northwestern University Kellogg Graduate School of Management, I worked in industry for ten years. I had the luck of being a financial controller at Fortune 100 corporation division and then becoming operations manager at the same location. I then had to “eat the financial data I was serving,” and it was a true wake-up call – much of the information was at best useless and at worst misleading. Later with Deloitte I was trained on the theory of constraints (TOC) methodology which indicted cost accounting as “enemy number one of productivity.” I learned about the shortcomings with how accountants make assumptions.

In 1988, when Professor Kaplan struck an exclusive relationship with KPMG Peat Marwick, I was recruited to KPMG with about three others with similar operational backgrounds as I to implement activity based cost management (ABC/M) systems but with using an ABC/M modeling software tool. I learned from experience. Four years later, my mentor Bob Bonsack, who had moved on from Deloitte to Electronic Data Systems (EDS) recruited me to head EDS’ cost management consulting. With about fifteen consultants, I was exposed to over a hundred implementations of cost systems. It was there that I experimented with creating a two day “ABC/M rapid prototyping” method that was radically different from the multi-month approach. By starting with a quick vision of what their ABC/M system would look like, companies could iteratively re-model to the level of detail, granularity, and accuracy needed to support analysis and decisions. It did not initially require a huge system, which was why some ABC/M system implementations got into trouble. My major self-realization is that costing is accomplished by modeling cost consumption relationships – an insight that continues to evade many accountants.

When I began to see the application of strategy maps and the balanced scorecard, more light bulbs went off in my brain. I then began truly seeing the organization as a “system” where all the performance improvement methodologies and core processes are inter-connected. I realized that the technologies are no longer the impediment because they are proven. The obstacle is the organization’s thinking – and the mindset of senior management who is presumably doing the leading.

My advice to high school students take your studies more seriously than you even imagine, and spend less time text-messaging everyone you know and focus on the more meaningful relationships. They will eventually be your friends rather than just acquaintances. And take math courses!

Ajay- So what exactly do you do at SAS? And name some interesting anecdotes that led to a lot of value as well as fun for both your company and clients. How does Gary spend his daily day at SAS Institute?

COKINS: My primary role with SAS is to create and deliver thought leadership content about Performance Management leveraging business analytics. I present webinars and write articles, blogs, presentations and also books. For the last four years I have averaged visiting roughly 40 international cities where SAS offices are located to present seminars and meet SAS customers to educate them on the concepts and benefits from Performance Management methodologies.

Recent examples of having fun and providing value to organizations involved providing expert advice to the International Monetary Fund (IMF) in Washington DC and the European Patent Office (EPO) in Brussels. The IMF is at the beginning of implementing an activity based cost management (ABC/M) system whereas the EPO is completing their ABC/M system design. Both organizations were seeking tips for success and pitfalls to avoid. One of my major recommendations was to not under-estimate the natural resistance to change of managers and employees. That is, they need to focus much more on getting their buy-in than worrying if the system is perfect. The value to them is realizing that Performance Management methodologies are much more social than technical.

Regarding my daily activities, when I am not traveling, I am mainly reading articles written by other experts or journalists and then translating my relevant takeaways into content that I can educate others with. I also respond to questions and requests both internally within SAS and externally from customers, management consultants, and university faculty.

Ajay- When you were a young employee, what was the toughest challenge that you faced? What was your worst mistake and how did you overcome it? What lessons did you learn from it?

COKINS: In my first few years in business following my university graduation, my toughest challenge was persuading my supervisors, usually older men than I, to accept my new ideas. I have always been a creative thinker, almost a dreamer; and I was not accustomed to the resistance that managers have to innovations, particularly those suggested by young inexperienced employees fresh from their university schooling.

My worst mistake was developing a computer program that automatically suggested treasury cash balance transfers to optimize the corporate cash management system of my first employer, a large Fortune 100 corporation. My computer program was basically replacing the decisions made by the corporate cash manager and part of his job. I overcame this disappointment by learning what needs the corporate cash manager did have and developing a different computer program that solved his needs. With its success, he eventually accepted the first computer program.

My lesson was one should first understand what people may want rather than trying to impose on them what you think they need without involving them.

Ajay- Looking back on your distinguished career, what project are you proud of the most? What project would you do over again if given the chance?

COKINS: In 1973 I became a financial controller of a large division of another Fortune 100 manufacturer. I created a rolling financial planning and forecast software program, using pre-spreadsheet software from a mainframe (years before personal computers and Excel). The program modeled product line sales forecasts by month and integrated both the income statement and balance sheet. It became a valuable tool for the executive team to suggest and immediately see varying sales levels as a “what if” scenario builder to calculate the different profit and working capital results. The executive team marveled at how analytical software, in contrast to our transactional ERP-like system, could make sense of the complexity of our operations with thousands of products and customers.

Regarding a project that fell short of expectations, I actually did get a chance to do it over again. As a consultant with Deloitte, I lead a project designing and implementing an activity based cost management (ABC/M) system using the client’s general ledger accounting software. It took many months, and when finished it was too complex for the client to fully understand. Several years later with a similar project I applied a rapid prototyping with iterative re-modeling approach that involved the company’s managers from the first day. (I mentioned this approach in my reply to the first question.) We completed the ABC/M system in just a few weeks, and everyone understood it and also how to interpret the information for analysis and decisions. I have since been a proponent of this type of rapid learning and system design approach.

Ajay- What do people do for fun at SAS Institute do when not creating or selling algorithms? How is SAS reaching out to other members of the analytics community in terms of basic science and development?

COKINS: SAS employees are inspired by our CEO, Dr. Jim Goodnight, who founded SAS roughly 35 years ago. Dr. Goodnight loves solving problems of all flavors. For fun, but also part of our jobs, SAS employees search for problems that only computer software can solve.

SAS’ offerings evolve by listening to our customers, who are typically scientists, researchers, and business analysts. Drug development and marketing analysts are examples. Our customers are our “community.” We motivate them, with formal methods of collecting input from them, to share with us enhancements to our future versions of our software.

Ajay- Describe your new book on Performance Management from the point of a beginner. Assume that I am a college student who does not know why I should read it. Then assume that I am a CIO and have little time to read it. What is in it for a CIO?

COKINS: This is my sixth book I have written. My first four books were about activity based cost management (ABC/M) and the last two about Performance Management. What is different about this second book is it immediately clarifies the confusion and ambiguity about what Performance Management is and is not. It is also written in a humorous and simplified way with lots of analogies and metaphors, such as all of the Performance Management methodologies integrated together like gears in an automobile engine and with a GPS for predictive navigation and dashboards for feedback. Beginners perceive each methodology, such as a balanced scorecard or customer relationship management system, are stand-alone tools. There is synergy when they are integrated.

cokins3

CIOs have similar needs. They need to shift their mindset from a technical one to a managerial one. Just a few chapters from this book can help CIOs see the broad picture of how all of their organizations processes fit together, and how they can be aligned to efficiently execute the ever-adjusting strategy that the executives continuously formulate with operations.


Biography and Contact Information

Gary Cokins, CPIM

(gary.cokins@sas.com; phone 919 531 2012)

http://blogs.sas.com/cokins

Gary Cokins is a global product marketing manager involved with performance management solutions with SAS, a leading provider of performance management and business analytics software headquartered in Cary, North Carolina. Gary is an internationally recognized expert, speaker, and author in advanced cost management and performance improvement systems. Gary received a BS degree with honors in Industrial Engineering/Operations Research from Cornell University in 1971. He received his MBA from Northwestern University’s Kellogg School of Management in 1974.

Gary began his career as a strategic planner FMC’s Link-Belt Division and then served as Financial Controller and Operations Manager. In 1981 Gary began his management consulting career first with Deloitte Consulting. Next with KPMG Peat Marwick, Gary was trained on ABC by Harvard Business School Professors Robert S. Kaplan and Robin Cooper. More recently, Gary headed the National Cost Management Consulting Services for Electronic Data Systems (EDS)/ A.T. Kearney.

Gary was the lead author of the acclaimed An ABC Manager’s Primer (ISBN 0-86641-220-4) sponsored by the Institute of Management Accountants (IMA). Gary’s second book, Activity Based Cost Management: Making it Work (ISBN 0-7863-0740-4), was judged by the Harvard Business School Press as “read this book first.” A reviewer for Gary’s third book, Activity Based Cost Management: An Executive’s Guide (ISBN 0-471-44328-X) said, Gary has the gift to take the concept that many view as complex and reduce it to its simplest terms.” This book was ranked number one in sales volume of 151 similar books on BarnesandNoble.com. Gary has also written Activity Based Cost Management in Government (ISBN 1-056726-110-8). His latest books are Performance Management: Finding the Missing Pieces to Close the Intelligence Gap (ISBN 0-471-57690-5) and Performance Management: Integrating Strategy Execution, Methodologies, Risk, and Analytics (ISBN 978-0-470-44998-1).

Mr. Cokins participates and serves on committees including: CAM-I, the Supply Chain Council, the International Federation of Accountants (IFAC), and the Institute of Management Accountants. Mr. Cokins is a member of Journal of Cost Management Editorial Advisory Board. Cokins can be reached at gary.cokins@sas.com . His blog is at http//:blogs.sas.com/cokins

and his latest book can also be previewed at http://www.sas.com/apps/pubscat/bookdetails.jsp?catid=1&pc=62401

Decisionstats Interviews

Here is a list of interviews that I have published- these are specific to analytics and data mining and include only the most recent interviews. If I have missed out any notable recent interview related to analytics and data mining, kindly do let me know. Hat Tip to Karl Rexer, for this suggestion .

Date    Name of Interviewee    Designation and Organization

09-Jun    Karl Rexer                          President, Rexer Analytics
05-Jun    Jim Daves                          CMO, SAS Institute
04-Jun    Paul van Eikeren                 President and CEO, Blue Reference
29-May    David Smith                      Director of Community, REvolution Computing
17-May    Dominic Pouzin                 CEO, Data Applied
11-May    Bruno Delahaye                 VP, KXEN
04-May    Ron Ramos                        Director, Zementis
30-Apr    Oliver Jouve                       VP, SPSS Inc
21-Apr    Fabian Dill                         Co- Founder, Knime.com
18-Apr    Alicia Mcgreevey                 Head Marketing, Visual Numerics
27-Mar    Francoise Soulie Fogelman    VP, KXEN
17-Mar    Jon Peck                            Principal Software Engineer, SPSS Inc
06-Mar    Anne Milley                        Director of product marketing, SAS Institute
04-Mar    Anne Milley                        Director of product marketing, SAS Institute
03-Feb    Phil Rack                            Creator, Bridge to R,and CEO Minequest
03-Feb    Michael Zeller                     CEO, Zementis
31-Jan    Richard Schultz                   CEO, Revolution Computing
21-Jan    Bob Muenchen                    Author, R for SAS and SPSS Users
13-Jan    Dr Graham Williams           Creator, Rattle GUI for R
05-Jan    Roger Haddad                    CEO, KXEN
26-Sep    June Dershewitz                  VP, Semphonic
04-Sep    Vincent Granville                 Head, Analyticbridge

The URl’s to specific interviews are also in this sheet.

http://spreadsheets.google.com/pub?key=rWTqcMe9mqwHeFv1e4GS_yg&single=true&gid=0&range=a1%3Ae24&output=html

KXEN Case Studies : Financial Sector

Here are the summaries of some excellent success stories that KXEN has achieved working with partners in the financial world over the years.

Fraud Modeling- Disbank (acquired by Fortis) Turkey

1. Dısbank increased the number of identified fraudulent applications by 200% from 7 to 21 per day.

2.More than 50 fraudsters using counterfeit cards at merchant locations or fraudulent applications have been arrested after April 2004 when the fraud modeling system was set.


A large Bank on the U.S. East Coast

1.Response Modeling

Previously it took the modeling group four weeks to build one model with several hundred variables, using traditional modeling tools. KXEN took one hour for the same problem and doubled the lift in the top decile because it included variables that had not been used for this business question before.

2.Data Quality

Building a Cross/Up-sell Model for a direct marketing campaign to high net worth customers, the modelers needed four weeks using 1500 variables. Again it took one hour with KXEN, which uncovered significant problems with some of the top predictive variables. Further investigation proved that these problems were created in the data merge of the mail file and response file, creating several “perfect” predictors. The model was re-run, removing these variables, and immediately put into production.

Le Crédit Lyonnais

1.Around 160 score models now built annually – compared to around 10 previously – for 130 direct marketing campaigns.
2.KXEN software has allowed LCL to drive up response rates, leading to more value-added services for customers.

Finansbank, Turkey

1.Within 4 months of starting the project to combat dormancy using KXEN’s solution, the bank had successfully reactivated half its previously dormant customers as per Kunter Kutluay, Finansbank Director of Marketing and Risk Analytics.

Bank Austria Creditanstalt , Austria

1.Some 4.5 terabytes of data are held in the bank’s operational systems, with a further 2 terabytes archived. Analytical models created in KXEN are automatically fed through the bank’s scoring engine in batches weekly
or monthly depending on the schema.

“But we are looking at a success rate of target customer deals in the area of three to five per cent with KXEN.
Before that, it was one per cent or less. ”
Werner Widhalm, Head of the Customer Knowledge Management Unit.

Barclays

1.Barclays’ Teradata warehouse holds information on some 14 million active customers, with data
on many different aspects of customer behaviour. Previously, analysts had to manually whittle down several thousand fields of data to a core of only a few hundred to fit the limitations of the modelling process. Now, all of the variables can be fed straight into the predictive model.

Summary– KXEN has achieved tremendous response in all aspects of data modelling in financial sector where time in building, deploying and analyzing model is much more crucial than many other sectors. I would be following this with other case studies on other KXEN successes across multiple domains.

Source – http://www.kxen.com/index.php?option=com_content&task=view&id=220&Itemid=786

Disclaimer- I am a social media consultant for KXEN.