Here is a webinar by Predictive Analytics World conference, sponsored by Netezza.
Introducing the first PAW Hosted eWebinar
The New Age of Analytical Marketing
– October 13 2010 at 2pm (EST)
The volume and variety of online customer data is growing exponentially as consumers continue to shift shopping, communication, social interaction, media consumption and more onto the web. This new customer information, coupled with new marketing channels such as social media and mobile, present marketers with a tremendous opportunity to create richer, more personalized experiences for customers while also increased sales and ROI.
Translate new online customer data and marketing channels into improved business results.
Make better use of customer analytics.
Explore the opportunities and challenges associated with today’s customer analytics best practices.
Moderator
Special Guest Speakers:
Eric Siegel, Ph.D. Founder
Predictive Analytics World
Vineet Singh Director Innovation, Analytics and Engineering
Intuit
Keynote Session by James Kobielus,
Senior Analyst at Forrester Research, Inc. and author
of “The Forrester WaveTM: Predictive Analytics & Data Mining Solutions, Q1 2010” report
11:30-12:05 AM
Customer Case Study: The European Commission (Government)
12:05-12:50 PM
General Session: Teradata Advanced Analytics
12:50-02:00 PM
Lunch Break & Exhibition
02:00-02:35 PM
Customer Case Study:
Virgin Media (Communications)
02:35-03:05 PM
General Session: Sponsor Presentation
03:05-03:40 PM
Coffee Break & Exhibition
03:40-04:40 PM
General Session: The Factory Approach to Compete on Analytics
04:40-05:25 PM
Customer Case Study: Insurance
05:30-06:30 PM
Cocktail & Exhibition
07:30-00:00 PM
Gala Dinner
FRIDAY, OCTOBER 29, 2010
08:30-09:00 AM
Registration & Breakfast
09:00-10:00 AM
Keynote Presentation: The CTO Talk
10:00-10:30 AM
Customer Case Study:
MonotaRO (Japan – Retail)
10:30-10:55 AM
Coffee Break & Exhibition
10:55-11:30 AM
General Session:
Sponsor Presentation
11:30-12:05 PM
Customer Case Study:
Aviva (Poland – Insurance)
12:05-01:00 PM
Lunch Break & Exhibition
01:00-01:45 PM
General Session:
How Social Network Analysis Can Boost your Marketing Performance
01:45-02:20 PM
Customer Case Study:
Financial Services
02:20-02:45 PM
Closing Remarks,
by John Ball, CEO KXEN
02:45-03:00 PM
Coffee Break & Exhibition
Optional: Technical Training (Complimentary to all Attendees)
02:45-04:00 PM
Hands-On Training #1: Getting Started with KXEN Analytical Data Management (ADM)
04:00-04:15 PM
Coffee Break
04:15-05:30 PM
Hands-On Training #2: Getting Started with KXEN Modeling Factory (KMF)
His argument of love is not very original though it was first made by these four guys
I am going to argue that “some” R developers should be paid, while the main focus should be volunteers code. These R developers should be paid as per usage of their packages.
Let me expand.
Imagine the following conversation between Ross Ihaka, Norman Nie and Peter Dalgaard.
Norman- Hey Guys, Can you give me some code- I got this new startup.
Ross Ihaka and Peter Dalgaard- Sure dude. Here is 100,000 lines of code, 2000 packages and 2 decades of effort.
Norman- Thanks guys.
Ross Ihaka- Hey, What you gonna do with this code.
Norman- I will better it. Sell it. Finally beat Jim Goodnight and his **** Proc GLM and **** Proc Reg.
Ross- Okay, but what will you give us? Will you give us some code back of what you improve?
Norman – Uh, let me explain this open core …
Peter D- Well how about some royalty?
Norman- Sure, we will throw parties at all conferences, snacks you know at user groups.
Ross – Hmm. That does not sound fair. (walks away in a huff muttering)-He takes our code, sells it and wont share the code
Peter D- Doesnt sound fair. I am back to reading Hamlet, the great Dane, and writing the next edition of my book. I am glad I wrote a book- Ross didnt even write that.
Norman-Uh Oh. (picks his phone)- Hey David Smith, We need to write some blog articles pronto – these open source guys ,man…
———–I think that sums what has been going on in the dynamics of R recently. If Ross Ihaka and R Gentleman had adopted an open core strategy- meaning you can create packages to R but not share the original where would we all be?
At this point if he is reading this, David Smith , long suffering veteran of open source flameouts is rolling his eyes while Tal G is wondering if he will publish this on R Bloggers and if so when or something.
Lets bring in another R veteran- Hadley Wickham who wrote a book on R and also created ggplot. Thats the best quality, most often used graphics package.
In terms of economic utilty to end user- the ggplot package may be as useful if not more as the foreach package developed by Revolution Computing/Analytics.
However lets come to open core licensing ( read it here http://alampitt.typepad.com/lampitt_or_leave_it/2008/08/open-core-licen.html ) which is where the debate is- Revolution takes code- enhances it (in my opinion) substantially with new formats XDF for better efficieny, web services API, and soon coming next year a GUI (thanks in advance , Dr Nie and guys)
and sells this advanced R code to businesses happy to pay ( they are currently paying much more to DR Goodnight and HIS guys)
Why would any sane customer buy it from Revolution- if he could download exactly the same thing from http://r-project.org
Hence the business need for Revolution Analytics to have an enhanced R- as they are using a product based software model not software as a service model.
If Revolution gives away source code of these new enhanced codes to R core team- how will R core team protect the above mentioned intelectual property- given they have 2 decades experience of giving away free code , and back and forth on just code.
Now Revolution also has a marketing budget- and thats how they sponsor some R Core events, conferences, after conference snacks.
How would people decide if they are being too generous or too stingy in their contribution (compared to the formidable generosity of SAS Institute to its employees, stakeholders and even third party analysts).
Would it not be better- IF Revolution can shift that aspect of relationship to its Research and Development budget than it’s marketing budget- come with some sort of incentive for “SOME” developers – even researchers need grants and assistantships, scholarships, make a transparent royalty formula say 17.5 % of the NEW R sales goes to R PACKAGE Developers pool, which in turn examines usage rate of packages and need/merit before allocation- that would require Revolution to evolve from a startup to a more sophisticated corporate and R Core can use this the same way as John M Chambers software award/scholarship
Dont pay all developers- it would be an insult to many of them – say Prof Harrell creator of HMisc to accept – but can Revolution expand its dev base (and prospect for future employees) by even sponsoring some R Scholarships.
And I am sure that if Revolution opens up some more code to the community- they would the rest of the world and it’s help useful. If it cant trust people like R Gentleman with some source code – well he is a board member.
——————————————————————————————–
Now to sum up some technical discussions on NeW R
1) An accepted way of benchmarking efficiencies.
2) Code review and incorporation of efficiencies.
3) Multi threading- Multi core usage are trends to be incorporated.
4) GUIs like R Commander E Plugins for other packages, and Rattle for Data Mining to have focussed (or Deducer). This may involve hiring User Interface Designers (like from Apple 😉 who will work for love AND money ( Even the Beatles charge royalty for that song)
5) More support to cloud computing initiatives like Biocep and Elastic R – or Amazon AMI for using cloud computers- note efficiency arguements dont matter if you just use a Chrome Browser and pay 2 cents a hour for an Amazon Instance. Probably R core needs more direct involvement of Google (Cloud OS makers) and Amazon as well as even Salesforce.com (for creating Force.com Apps). Note even more corporates here need to be involved as cloud computing doesnot have any free and open source infrastructure (YET)
“If something goes wrong with Microsoft, I can phone Microsoft up and have it fixed. With Open Source, I have to rely on the community.”
And the community, as much as we may love it, is unpredictable. It might care about your problem and want to fix it, then again, it may not. Anyone who has ever witnessed something online go “viral”, good or bad, will know what I’m talking about.
Predictive Analytics World ( http://pawcon.com ) is the business-focused event for predictive analytics professionals, managers and commercial practitioners, covering today’s commercial deployment of predictive analytics, across industries and across software vendors.
PAW delivers the best case studies, expertise, keynotes, sessions, workshops, exposition, expert panel, live demos, networking coffee breaks, reception, birds-of-a-feather lunches, brand-name enterprise leaders, and industry heavyweights in the business.
Case study presentations cover campaign targeting, churn modeling, next-best-offer, selecting marketing channels, global analytics deployment, email marketing, HR candidate search, and other innovative applications. The Conference agendas cover hot topics such as social data, text mining, search marketing, risk management, uplift (incremental lift) modeling, survey analysis, consumer privacy, sales force optimization and other innovative applications that benefit organizations in new and creative ways.
PAW delivers two rich conference programs in Oct./Nov. with very little content overlap featuring a wealth of speakers with front-line experience. See which one is best for you:
PAW’s DC 2010 (Oct 19-20) program includes over 25 sessions across two tracks – an “All Audiences” and an “Expert/Practitioner” track — so you can witness how predictive analytics is applied at 1-800-FLOWERS, CIBC, Corporate Executive Board, Forrester, LifeLine, Macy’s, MetLife, Miles Kimball, Monster, Paychex, PayPal (eBay), SunTrust, Target, UPMC Health Plan, Xerox, YMCA, and Yahoo!, plus special examples from the U.S. government agencies DoD, DHS, and SSA.
PAW London 2010 (Nov 15-16) will feature over 20 speakers from 10 countries with case studies from leading enterprises in e-commerce, finance, healthcare, retail, and telecom such as Canadian Automobile Association, Chessmetrics, e-Dialog, Hamburger Sparkasse, Jeevansathi.com (India’s 2nd-largest matrimony portal), Life Line Screening, Lloyds TSB, Naukri.com (India’s number 1 job portal), Overtoom, SABMiller, Univ. of Melbourne, and US Bank, plus special examples from Anheuser-Busch, Disney, HP, HSBC, Pfizer, U.S. SSA, WestWind Foundation and others.
If you wish to receive periodic call-for-speakers notifications regarding Predictive Analytics World, email chair@predictiveanalyticsworld.com with the subject line “call-for-speakers notifications”.
Interestingly (and not surprisingly) Revolution Analytics is teaming up with Jaspersoft to use R for reporting along with the Jaspersoft BI stack.
ADVANCED ANALYTICS ON DEMAND IN APPLICATIONS, IN DASHBOARDS, AND ON THE WEB
FREE WEBINAR WEDNESDAY, SEPTEMBER 22ND @9AM PACIFIC
DEPLOYING R: ADVANCED ANALYTICS ON DEMAND IN APPLICATIONS, IN DASHBOARDS, AND ON THE WEB
A JOINT WEBINAR FROM REVOLUTION ANALYTICS AND JASPERSOFT
Date:
Wednesday, September 22, 2010
Time:
9:00am PDT (12:00pm EDT; 4:00pm GMT)
Presenters:
David Smith, Vice President of Marketing, Revolution Analytics
Andrew Lampitt, Senior Director of Technology Alliances, Jaspersoft
Matthew Dahlman, Business Development Engineer, Jaspersoft
R is a popular and powerful system for creating custom data analysis, statistical models, and data visualizations. But how can you make the results of these R-based computations easily accessible to others? A PhD statistician could use R directly to run the forecasting model on the latest sales data, and email a report on request, but then the process is just going to have to be repeated again next month, even if the model hasn’t changed. Wouldn’t it be better to empower the Sales manager to run the model on demand from within the BI application she already uses—daily, even!—and free up the statistician to build newer, better models for others?
In this webinar, David Smith (VP of Marketing, Revolution Analytics) will introduce the new “RevoDeployR” Web Services framework for Revolution R Enterprise, which is designed to make it easy to integrate dynamic R-based computations into applications for business users. RevoDeployR empowers data analysts working in R to publish R scripts to a server-based installation of Revolution R Enterprise. Application developers can then use the RevoDeployR Web Services API to securely and scalably integrate the results of these scripts into any application, without needing to learn the R language. With RevoDeployR, authorized users of hosted or cloud-based interactive Web applications, desktop applications such as Microsoft Excel, and BI applications like Jaspersoft can all benefit from on-demand analytics and visualizations developed by expert R users.
To demonstrate the power of deploying R-based computations to business users, Andrew Lampitt will introduce Jaspersoft commercial open source business intelligence, the world’s most widely used BI software. In a live demonstration, Matt Dahlman will show how to supercharge the BI process by combining Jaspersoft and Revolution R Enterprise, giving business users on-demand access to advanced forecasts and visualizations developed by expert analysts.
David Smith is the Vice President of Marketing at Revolution Analytics, the leading commercial provider of software and support for the open source “R” statistical computing language. David is the co-author (with Bill Venables) of the official R manual An Introduction to R. He is also the editor of Revolutions (http://blog.revolutionanalytics.com), the leading blog focused on “R” language, and one of the originating developers of ESS: Emacs Speaks Statistics. You can follow David on Twitter as @revodavid.
Andrew Lampitt is Senior Director of Technology Alliances at Jaspersoft. Andrew is responsible for strategic initiatives and partnerships including cloud business intelligence, advanced analytics, and analytic databases. Prior to Jaspersoft, Andrew held other business positions with Sunopsis (Oracle), Business Objects (SAP), and Sybase (SAP). Andrew earned a BS in engineering from the University of Illinois at Urbana Champaign.
Matthew Dahlman is Jaspersoft’s Business Development Engineer, responsible for technical aspects of technology alliances and regional business development. Matt has held a wide range of technical positions including quality assurance, pre-sales, and technical evangelism with enterprise software companies including Sybase, Netonomy (Comverse), and Sunopsis (Oracle). Matt earned a BA in mathematics from Carleton College in Northfield, Minnesota.
The second widely used BI stack in open source is Pentaho.
You can download it here to evaluate it or click on screenshot to read more at
Here is an interview with Stephanie McReynolds who works as as Director of Product Marketing with AsterData. I asked her a couple of questions about the new product releases from AsterData in analytics and MapReduce.
Ajay – How does the new Eclipse Plugin help people who are already working with huge datasets but are new to AsterData’s platform?
Stephanie- Aster Data Developer Express, our new SQL-MapReduce development plug-in for Eclipse, makes MapReduce applications easy to develop. With Aster Data Developer Express, developers can develop, test and deploy a complete SQL-MapReduce application in under an hour. This is a significant increase in productivity over the traditional analytic application development process for Big Data applications, which requires significant time coding applications in low-level code and testing applications on sample data.
Ajay – What are the various analytical functions that are introduced by you recently- list say the top 10.
Stephanie- At Aster Data, we have an intense focus on making the development process easier for SQL-MapReduce applications. Aster Developer Express is a part of this initiative, as is the release of pre-defined analytic functions. We recently launched both a suite of analytic modules and a partnership program dedicated to delivering pre-defined analytic functions for the Aster Data nCluster platform. Pre-defined analytic functions delivered by Aster Data’s engineering team are delivered as modules within the Aster Data Analytic Foundation offering and include analytics in the areas of pattern matching, clustering, statistics, and text analysis– just to name a few areas. Partners like Fuzzy Logix and Cobi Systems are extending this library by delivering industry-focused analytics like Monte Carlo Simulations for Financial Services and geospatial analytics for Public Sector– to give you a few examples.
Ajay – So okay I want to do a K Means Cluster on say a million rows (and say 200 columns) using the Aster method. How do I go about it using the new plug-in as well as your product.
Stephanie- The power of the Aster Data environment for analytic application development is in SQL-MapReduce. SQL is a powerful analytic query standard because it is a declarative language. MapReduce is a powerful programming framework because it can support high performance parallel processing of Big Data and extreme expressiveness, by supporting a wide variety of programming languages, including Java, C/C#/C++, .Net, Python, etc. Aster Data has taken the performance and expressiveness of MapReduce and combined it with the familiar declarativeness of SQL. This unique combination ensures that anyone who knows standard SQL can access advanced analytic functions programmed for Big Data analysis using MapReduce techniques.
kMeans is a good example of an analytic function that we pre-package for developers as part of the Aster Data Analytic Foundation. What does that mean? It means that the MapReduce portion of the development cycle has been completed for you. Each pre-packaged Aster Data function can be called using standard SQL, and executes the defined analytic in a fully parallelized manner in the Aster Data database using MapReduce techniques. The result? High performance analytics with the expressiveness of low-level languages accessed through declarative SQL.
Ajay – I see an an increasing focus on Analytics. Is this part of your product strategy and how do you see yourself competing with pure analytics vendors.
Stephanie – Aster Data is an infrastructure provider. Our core product is a massively parallel processing database called nCluster that performs at or beyond the capabilities of any other analytic database in the market today. We developed our analytics strategy as a response to demand from our customers who were looking beyond the price/performance wars being fought today and wanted support for richer analytics from their database provider. Aster Data analytics are delivered in nCluster to enable analytic applications that are not possible in more traditional database architectures.
Ajay – Name some recent case studies in Analytics of implementation of MR-SQL with Analytical functions
Stephanie – There are three new classes of applications that Aster Data Express and Aster Analytic Foundation support: iterative analytics, prediction and optimization, and ad hoc analysis.
Aster Data customers are uncovering critical business patterns in Big Data by performing hypothesis-driven, iterative analytics. They are exploring interactively massive volumes of data—terabytes to petabytes—in a top-down deductive manner. ComScore, an Aster Data customer that performs website experience analysis is a good example of an Aster Data customer performing this type of analysis.
Other Aster Data customers are building applications for prediction and optimization that discover trends, patterns, and outliers in data sets. Examples of these types of applications are propensity to churn in telecommunications, proactive product and service recommendations in retail, and pricing and retention strategies in financial services. Full Tilt Poker, who is using Aster Data for fraud prevention is a good example of a customer in this space.
The final class of application that I would like to highlight is ad hoc analysis. Examples of ad hoc analysis that can be performed includes social network analysis, advanced click stream analysis, graph analysis, cluster analysis and a wide variety of mathematical, trigonometry, and statistical functions. LinkedIn, whose analysts and data scientists have access to all of their customer data in Aster Data are a good example of a customer using the system in this manner.
While Aster Data customers are using nCluster in a number of other ways, these three new classes of applications are areas in which we are seeing particularly innovative application development.
Biography-
Stephanie McReynolds is Director of Product Marketing at Aster Data, where she is an evangelist for Aster Data’s massively parallel data-analytics server product. Stephanie has over a decade of experience in product management and marketing for business intelligence, data warehouse, and complex event processing products at companies such as Oracle, Peoplesoft, and Business Objects. She holds both a master’s and undergraduate degree from Stanford University.
None of the sites I checked clearly identify the work as having been sponsored in any way I found obvious in my (admittefly) quick scan. So this is an issue, but it’s not confined to Oracle.
My 2 cents (not being so well paid 😉 are-
I think Curt was calling out Oracle (which didnt respond) and not Merv ( whose subsequent blog post does much to clarify).
As a comparative new /younger blogger in this field,
I applaud both Curt to try and bell the cat ( or point out what everyone in AR winks at) and for Merv for standing by him.
In the long run, it would strengthen analyst relations as a channel if they separate financial payment of content from bias. An example is credit rating agencies who forgot to do so in BFSI and see what happened.
Customers invest millions of dollars in BI systems trusting marketing collateral/white papers/webinars/tests etc. Perhaps it’s time for an industry association for analysts so that individual analysts don’t knuckle down under vendor pressure.
It is easier for someone of Curt, Merv’s stature to declare editing policy and disclosures before they write a white paper.It is much harder for everyone else who is not so well established.
White papers can take as much as 25,000$ to produce- and I know people who in Business Analytics (as opposed to Business Intelligence) slog on cents per hour cranking books on R, SAS , webinars, trainings but there are almost no white papers in BA. Are there any analytics independent analysts who are not biased by R or SAS or SPSS or etc etc. I am not sure but this looks like a good line to pursue 😉 – provided ethical checks and balances are established.
Personally I know of many so called analytics communities go all out to please their sponsors so bias in writing does exist (you cant praise SAS on a R Blogging Forum or R USers Meet and you cant write on WPS at SAS Community.org )
– at the same time someone once told me- It is tough to make a living as a writer, and that choice between easy money and credible writing needs to be respected.
Most sponsored white papers I read are pure advertisements, directed at CEOs rather than the techie community at large.
Almost every BI vendor claims to have the fastest database with 5X speed- and benchmarking in technical terms could be something they could do too.
Just like Gadget sites benchmark products, you can not benchmark BI or even BA products as it is written not to do so in many licensing terms.
Probably that is the reason Billions are spent in BI and the positive claims are doubtful ( except by the sellers). Similarly in Analytics, many vendors would have difficulty justifying their claims or prices if they are subjected to a side by side comparison. Unfortunately the resulting confusion results in shoddy technology coming stronger due to more aggressive marketing.
DECISION STATS 