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Access PAW DC Session Videos Now
Predictive Analytics World is pleased to announce on-demand access to the videos of PAW Washington DC, October 2010, including over 30 sessions and keynotes that you may view at your convenience. Access this leading predictive analytics content online now:
Select individual conference sessions, or recognize savings by registering for access to one or two full days of sessions. These on-demand videos deliver PAW DC right to your desk, covering hot topics and advanced methods such as:
PAW DC videos feature over 25 speakers with case studies from leading enterprises such as: CIBC, CEB, Forrester, Macy’s, MetLife, Microsoft, Miles Kimball, Monster.com, Oracle, Paychex, SunTrust, Target, UPMC, Xerox, Yahoo!, YMCA, and more.
Keynote: Five Ways Predictive Analytics Cuts Enterprise Risk
Eric Siegel,Ph.D., Program Chair, Predictive Analytics World
All business is an exercise in risk management. All organizations would benefit from measuring, tracking and computing risk as a core process, much like insurance companies do.
Predictive analytics does the trick, one customer at a time. This technology is a data-driven means to compute the risk each customer will defect, not respond to an expensive mailer, consume a retention discount even if she were not going to leave in the first place, not be targeted for a telephone solicitation that would have landed a sale, commit fraud, or become a “loss customer” such as a bad debtor or an insurance policy-holder with high claims.
In this keynote session, Dr. Eric Siegel reveals:
– Five ways predictive analytics evolves your enterprise to reduce risk
– Hidden sources of risk across operational functions
– What every business should learn from insurance companies
– How advancements have reversed the very meaning of fraud
– Why “man + machine” teams are greater than the sum of their parts for enterprise decision support
Platinum Sponsor Presentation: Analytics – The Beauty of Diversity
Anne H. Milley,Senior Director of Analytic Strategy, Worldwide Product Marketing, SAS
Analytics contributes to, and draws from, multiple disciplines. The unifying theme of “making the world a better place” is bred from diversity. For instance, the same methods used in econometrics might be used in market research, psychometrics and other disciplines. In a similar way, diverse paradigms are needed to best solve problems, reveal opportunities and make better decisions. This is why we evolve capabilities to formulate and solve a wide range of problems through multiple integrated languages and interfaces. Extending that, we have provided integration with other languages so that users can draw on the disciplines and paradigms needed to best practice their craft.
Gold Sponsor Presentation: Predictive Analytics Accelerate Insight for Financial Services
Finbarr Deely,Director of Business Development,ParAccel
Financial services organizations face immense hurdles in maintaining profitability and building competitive advantage. Financial services organizations must perform “what-if” scenario analysis, identify risks, and detect fraud patterns. The advanced analytic complexity required often makes such analysis slow and painful, if not impossible. This presentation outlines the analytic challenges facing these organizations and provides a clear path to providing the accelerated insight needed to perform in today’s complex business environment to reduce risk, stop fraud and increase profits. * The value of predictive analytics in Accelerating Insight * Financial Services Analytic Case Studies * Brief Overview of ParAccel Analytic Database
TOPIC: SURVEY ANALYSIS Case Study: YMCA Turning Member Satisfaction Surveys into an Actionable Narrative
Dean Abbott,President, Abbott Analytics
Employees are a key constituency at the Y and previous analysis has shown that their attitudes have a direct bearing on Member Satisfaction. This session will describe a successful approach for the analysis of YMCA employee surveys. Decision trees are built and examined in depth to identify key questions in describing key employee satisfaction metrics, including several interesting groupings of employee attitudes. Our approach will be contrasted with other factor analysis and regression-based approaches to survey analysis that we used initially. The predictive models described are currently in use and resulted in both greater understanding of employee attitudes, and a revised “short-form” survey with fewer key questions identified by the decision trees as the most important predictors.
TOPIC: INDUSTRY TRENDS 2010 Data Minter Survey Results: Highlights
Karl Rexer,Ph.D., Rexer Analytics
Do you want to know the views, actions, and opinions of the data mining community? Each year, Rexer Analytics conducts a global survey of data miners to find out. This year at PAW we unveil the results of our 4th Annual Data Miner Survey. This session will present the research highlights, such as:
Multiple Case Studies: U.S. DoD, U.S. DHS, SSA Text Mining: Lessons Learned
John F. Elder,Chief Scientist, Elder Research, Inc.
Text Mining is the “Wild West” of data mining and predictive analytics – the potential for gain is huge, the capability claims are often tall tales, and the “land rush” for leadership is very much a race.
In solving unstructured (text) analysis challenges, we found that principles from inductive modeling – learning relationships from labeled cases – has great power to enhance text mining. Dr. Elder highlights key technical breakthroughs discovered while working on projects for leading government agencies, including: Text Mining is the “Wild West” of data mining and predictive analytics – the potential for gain is huge, the capability claims are often tall tales, and the “land rush” for leadership is very much a race.
– Prioritizing searches for the Dept. of Homeland Security
– Quick decisions for Social Security Admin. disability
– Document discovery for the Dept. of Defense
– Disease discovery for the Dept. of Homeland Security
Keynote: How Target Gets the Most out of Its Guest Data to Improve Marketing ROI
Andrew Pole,Senior Manager, Media and Database Marketing, Target
In this session, you’ll learn how Target leverages its own internal guest data to optimize its direct marketing – with the ultimate goal of enhancing our guests’ shopping experience and driving in-store and online performance. You will hear about what guest data is available at Target, how and where we collect it, and how it is used to improve the performance and relevance of direct marketing vehicles. Furthermore, we will discuss Target’s development and usage of guest segmentation, response modeling, and optimization as means to suppress poor performers from mailings, determine relevant product categories and services for online targeted content, and optimally assign receipt marketing offers to our guests when offer quantities are limited.
Platinum Sponsor Presentation: Driving Analytics Into Decision Making
Jason Verlen,Director, SPSS Product Strategy & Management, IBM Software Group
Organizations looking to dramatically improve their business outcomes are turning to decision management, a convergence of technology and business processes that is used to streamline and predict the outcome of daily decision-making. IBM SPSS Decision Management technology provides the critical link between analytical insight and recommended actions. In this session you’ll learn how Decision Management software integrates analytics with business rules and business applications for front-line systems such as call center applications, insurance claim processing, and websites. See how you can improve every customer interaction, minimize operational risk, reduce fraud and optimize results.
TOPIC: DATA INFRASTRUCTURE AND INTEGRATION Case Study: Macy’s The world is not flat (even though modeling software has to think it is)
Paul Coleman,Director of Marketing Statistics, Macy’s Inc.
Software for statistical modeling generally use flat files, where each record represents a unique case with all its variables. In contrast most large databases are relational, where data are distributed among various normalized tables for efficient storage. Variable creation and model scoring engines are necessary to bridge data mining and storage needs. Development datasets taken from a sampled history require snapshot management. Scoring datasets are taken from the present timeframe and the entire available universe. Organizations, with significant data, must decide when to store or calculate necessary data and understand the consequences for their modeling program.
TOPIC: CUSTOMER VALUE Case Study: SunTrust When One Model Will Not Solve the Problem – Using Multiple Models to Create One Solution
Dudley Gwaltney,Group Vice President, Analytical Modeling, SunTrust Bank
In 2007, SunTrust Bank developed a series of models to identify clients likely to have large changes in deposit balances. The models include three basic binary and two linear regression models.
Based on the models, 15% of SunTrust clients were targeted as those most likely to have large balance changes. These clients accounted for 65% of the absolute balance change and 60% of the large balance change clients. The targeted clients are grouped into a portfolio and assigned to individual SunTrust Retail Branch. Since 2008, the portfolio generated a 2.6% increase in balances over control.
Using the SunTrust example, this presentation will focus on:
TOPIC: RESPONSE & CROSS-SELL Case Study: Paychex Staying One Step Ahead of the Competition – Development of a Predictive 401(k) Marketing and Sales Campaign
Jason Fox,Information Systems and Portfolio Manager,Paychex
In-depth case study of Paychex, Inc. utilizing predictive modeling to turn the tides on competitive pressures within their own client base. Paychex, a leading provider of payroll and human resource solutions, will guide you through the development of a Predictive 401(k) Marketing and Sales model. Through the use of sophisticated data mining techniques and regression analysis the model derives the probability a client will add retirement services products with Paychex or with a competitor. Session will include roadblocks that could have ended development and ROI analysis. Speaker: Frank Fiorille, Director of Enterprise Risk Management, Paychex Speaker: Jason Fox, Risk Management Analyst, Paychex
TOPIC: SEGMENTATION Practitioner: Canadian Imperial Bank of Commerce Segmentation Do’s and Don’ts
Daymond Ling,Senior Director, Modelling & Analytics,Canadian Imperial Bank of Commerce
The concept of Segmentation is well accepted in business and has withstood the test of time. Even with the advent of new artificial intelligence and machine learning methods, this old war horse still has its place and is alive and well. Like all analytical methods, when used correctly it can lead to enhanced market positioning and competitive advantage, while improper application can have severe negative consequences.
This session will explore what are the elements of success, and what are the worse practices that lead to failure. The relationship between segmentation and predictive modeling will also be discussed to clarify when it is appropriate to use one versus the other, and how to use them together synergistically.
TOPIC: SOCIAL DATA
Thought Leadership Social Network Analysis: Killer Application for Cloud Analytics
James Kobielus,Senior Analyst, Forrester Research
Social networks such as Twitter and Facebook are a potential goldmine of insights on what is truly going through customers´minds. Every company wants to know whether, how, how often, and by whom they´re being mentioned across the billowing new cloud of social media. Just as important, every company wants to influence those discussions in their favor, target new business, and harvest maximum revenue potential. In this session, Forrester analyst James Kobielus identifies fruitful applications of social network analysis in customer service, sales, marketing, and brand management. He presents a roadmap for enterprises to leverage their inline analytics initiatives and leverage high-performance data warehousing (DW) clouds and appliances in order to analyze shifting patterns of customer sentiment, influence, and propensity. Leveraging Forrester’s ongoing research in advanced analytics and customer relationship management, Kobielus will discuss industry trends, commercial modeling tools, and emerging best practices in social network analysis, which represents a game-changing new discipline in predictive analytics.
Trish Mathe,
Director of Database Marketing, Life Line Screening
While Life Line is successfully executing a US CRM roadmap, they are also beginning this same evolution abroad. They are beginning in the UK where Merkle procured data and built a response model that is pulling responses over 30% higher than competitors. This presentation will give an overview of the US CRM roadmap, and then focus on the beginning of their strategy abroad, focusing on the data procurement they could not get anywhere else but through Merkle and the successful modeling and analytics for the UK. Speaker: Ozgur Dogan, VP, Quantitative Solutions Group, Merkle Inc Speaker: Trish Mathe, Director of Database Marketing, Life Line Screening
TOPIC: SURVEY ANALYSIS Case Study: Forrester Making Survey Insights Addressable and Scalable – The Case Study of Forrester’s Technographics Benchmark Survey
Marketers use surveys to create enterprise wide applicable strategic insights to: (1) develop segmentation schemes, (2) summarize consumer behaviors and attitudes for the whole US population, and (3) use multiple surveys to draw unified views about their target audience. However, these insights are not directly addressable and scalable to the whole consumer universe which is very important when applying the power of survey intelligence to the one to one consumer marketing problems marketers routinely face. Acxiom partnered with Forrester Research, creating addressable and scalable applications of Forrester’s Technographics Survey and applied it successfully to a number of industries and applications.
TOPIC: HEALTHCARE Case Study: UPMC Health Plan A Predictive Model for Hospital Readmissions
Scott Zasadil,Senior Scientist, UPMC Health Plan
Hospital readmissions are a significant component of our nation’s healthcare costs. Predicting who is likely to be readmitted is a challenging problem. Using a set of 123,951 hospital discharges spanning nearly three years, we developed a model that predicts an individual’s 30-day readmission should they incur a hospital admission. The model uses an ensemble of boosted decision trees and prior medical claims and captures 64% of all 30-day readmits with a true positive rate of over 27%. Moreover, many of the ‘false’ positives are simply delayed true positives. 53% of the predicted 30-day readmissions are readmitted within 180 days.
Here is a brief one question interview with James Kobielus, Senior Analyst, Forrester.
Ajay-Describe the five most important events in Predictive Analytics you saw in 2010 and the top three trends in 2011 as per you.
Jim-
Five most important developments in 2010:
Continued emergence of enterprise-grade Hadoop solutions as the core of the future cloud-based platforms for advanced analytics
Development of the market for analytic solution appliances that incorporate several key features for advanced analytics: massively parallel EDW appliance, in-database analytics and data management function processing, embedded statistical libraries, prebuilt logical domain models, and integrated modeling and mining tools
Integration of advanced analytics into core BI platforms with user-friendly, visual, wizard-driven, tools for quick, exploratory predictive modeling, forecasting, and what-if analysis by nontechnical business users
Convergence of predictive analytics, data mining, content analytics, and CEP in integrated tools geared to real-time social media analytics
Emergence of CRM and other line-of-business applications that support continuously optimized “next-best action” business processes through embedding of predictive models, orchestration engines, business rules engines, and CEP agility
Three top trends I see in the coming year, above and beyond deepening and adoption of the above-bulleted developments:
All-in-memory, massively parallel analytic architectures will begin to gain a foothold in complex EDW environments in support of real-time elastic analytics
Further crystallization of a market for general-purpose “recommendation engines” that, operating inline to EDWs, CEP environments, and BPM platforms, enable “next-best action” approaches to emerge from today’s application siloes
Incorporation of social network analysis functionality into a wider range of front-office business processes to enable fine-tuned behavioral-based customer segmentation to drive CRM optimization
James serves Business Process & Applications professionals. He is a leading expert on data warehousing, predictive analytics, data mining, and complex event processing. In addition to his core coverage areas, James contributes to Forrester’s research in business intelligence, data integration, data quality, and master data management.
PREVIOUS WORK EXPERIENCE
James has a long history in IT research and consulting and has worked for both vendors and research firms. Most recently, he was at Current Analysis, an IT research firm, where he was a principal analyst covering topics ranging from data warehousing to data integration and the Semantic Web. Prior to that position, James was a senior technical systems analyst at Exostar (a hosted supply chain management and eBusiness hub for the aerospace and defense industry). In this capacity, James was responsible for identifying and specifying product/service requirements for federated identity, PKI, and other products. He also worked as an analyst for the Burton Group and was previously employed by LCC International, DynCorp, ADEENA, International Center for Information Technologies, and the North American Telecommunications Association. He is both well versed and experienced in product and market assessments. James is a widely published business/technology author and has spoken at many industry events
1100 “Friends” on Facebook, and 9429 “Connections” on Linkedin
Deleting Facebook was an emotionally wrenching decision- see this screenshot- I tried to download all my account- family photos (320 mb) but connection kept breaking-
so I had just deactivate and not delete the account. You win, Zuckenberg
How to-
Right Hand Top Corner —-Account Settings- Deactivate Account
After Facebook de activates your account- it mocks you by saying this this in YELLOW “
Your Facebook account has been deactivated.
To reactivate your account, log in using your old login email and password. You will be able to use the site like you used to.
We hope you come back soon.”
I go back to Facebook to download all my family photos before final deletion (and not just de activation)- I get this message
It may take a little while for us to gather all of your photos, wall posts, messages, and other information. We will then ask you to verify your identity in order to help protect the security of your account.
Are you sure you don’t want to reconsider? Was it something we said? Tell us.
Before you deactivate your account, know this:
This action is permanent: account restoration is currently disabled.
You do not need to deactivate your account to change your username. (You can change it on the settings page. All @replies and followers will remain unchanged.)
Your account may be viewable on twitter.com for a few days after deactivation.
We have no control over content indexed by search engines like Google.
If you’re creating a new account and want to use the same user name, phone number and/or email address associated with this account, you must first change them on this account before you deactivate it. If you don’t, the information will be tied to this account and unavailable for use.
Okay, fine, deactivate my account (thats the button)
I clicked the Okay fine Button.
One more pop up-
Re-enter your Twitter password to deactivate @DecisionStats.
Ok Done-
Twitter tries to scare me again —-
You deactivated your account.
Account restoration is currently unavailable. Here is the message you agreed to before deactivating your account:
his action is permanent.
Before you deactivate your account, know this:
This action is permanent: account restoration is currently disabled.
You do not need to deactivate your account to change your username. (You can change it on the settings page. All @replies and followers will remain unchanged.)
Your account may be viewable on twitter.com for a few days after deactivation.
We have no control over content indexed by search engines like Google.
If you’re creating a new account and want to use the same user name, phone number and/or email address associated with this account, you must first change them on this account before you deactivate it. If you don’t, the information will be tied to this account and unavailable for use.
So Long Twitter, I gotta spend more time with my offline family okay.
And probably anyone trying to do sentiment analysis on my twitter feed for social media analytics now has an incomplete data point (hehe)
Last One- Linkedin 9349 connections are valuable- I was thinking of auctioning this on E Bay but they kicked me out.
So I just go for deletion.
I spend 10 minuted looking for the delete account button-this is getting a bit annoying now.
Linkedin neither scares me nor emotionally coddles me – This is what is says-
Closing Your Account
How do I close my account?
Log into the account you wish to close.
Hover your cursor over your name in the top right of your home page and then click “Settings”.
Click on “Close Your Account” under Personal Information.
Select a reason for closing your account.
Click on “Continue”.
Members should only have one LinkedIn account. Multiple accounts can prevent the ability to accept an Invitation. Closing additional accounts should resolve this dilemma. Prior to closing any secondary accounts:
Inventory all connections and identify any that may be missing from the primary account you wish to keep.
Send Invitations to those connections missing from the primary account.
Update any profile information that maybe on other account profiles.
I dont think I will send that many invites again- but some of these people have been good to me ( 18 of them even wrote recommendations- which are non exportable it seems)
I check my downloaded csv file- yup all 9379 email addresses are there.
Final round-
Update- Linkedin does NOT get deleted. I get this-
Your close account request must be processed by customer support for the following reason:
You have more than 250 connections.
You will receive a confirmation email from customer support indicating that they received your request to close your account.
The account that customer support will process for closure is below:
Ajay Ohri
9,429 Connections
16 Recommendations
ohri2007@gmail.com (primary address)
and the email says
Member Comment: ajay ohri
11/24/2010 23:10
Member ID: 6691344 Member Name: Ajay Ohri
The member has attempted to self close this account and was unable because:
The member has a large network of connections to close. Please close during non peak hours.
Please confirm with the member when his or her account has been successfully closed.
So long people- you know where to find me- on this blog (and some on skype).
Using WP- Stats I set about answering this question-
What search keywords lead here-
Clearly Michael Jackson is down this year
And R GUI, Data Mining is up.
How does that affect my writing- given I get almost 250 visitors by search engines alone daily- assume I write nothing on this blog from now on.
It doesnt- I still write what ever code or poem that comes to my mind. So it is hurtful people misunderstimate the effort in writing and jump to conclusions (esp if I write about a company- I am not on payroll of that company- just like if I write about a poem- I am not a full time poet)
Over to xkcd
All Time (for Decisionstats.Wordpress.com)
Search
Views
libre office
818
facebook analytics
806
michael jackson history
240
wps sas lawsuit
180
r gui
168
wps sas
154
wordle.net
118
sas wps
116
decision stats
110
sas wps lawsuit
100
google maps jet ski
94
data mining
88
doug savage
72
hive tutorial
63
spss certification
63
hadley wickham
63
google maps jetski
62
sas sues wps
60
decisionstats
58
donald farmer microsoft
45
libreoffice
44
wps statistics
44
best statistics software
42
r gui ubuntu
41
rstat
37
tamilnadu advanced technical training institute tatti
Here is a set of very nice, screenshot enabled tutorials from SAP BI. They are a bit outdated (3 years old) but most of it is quite relevant- especially from a Tutorial Design Perspective –
Most people would rather see screenshot based step by step powerpoints, than cluttered or clever presentations , or even videos that force you to sit like a TV zombie. Unfortunately most tutorial presentations I see especially for BI are either slides with one or two points, that abruptly shift to “concepts” or videos that are atleast more than 10 minutes long. That works fine for scripting tutorials or hands on workshops, but cannot be reproduced for later instances of study.
The mode of tutorials especially for GUI software can vary, it may be Slideshare, Scribd, Google Presentation,Microsoft Powerpoint but a step by step screenshot by screenshot tutorial is much better for understanding than commando line jargon/ Youtub Videos presentations, or Powerpoint with Points.
Have a look at these SAP BI 7 slideshares
and
Speaking of BI, the R Package called Brew is going to brew up something special especially combined with R Apache. However I wish R Apache, or R Web, or RServe had step by step install screenshot tutorials to increase their usage in Business Intelligence.
I tried searching for JMP GUI Tutorials too, but I believe putting all your content behind a registration wall is not so great. Do a Pareto Analysis of your training material, surely you can share a couple more tutorials without registration. It also will help new wanna-migrate users to get a test and feel for the installation complexities as well as final report GUI.
is it the russians doing a link spam. unlikely they dont bot against Akismet that much (as they fail)
And Captcha can be failed by python (apparently. sigh)
Is there a co relation of certain tags of posts, and count of spam- hoping to distort say blogs’s search engine rankings for SAS WPS Lawsuit in Google or jet ski across pacific in Google.
Sigh- an old retired outlaw black hat is never kept in peace. Try doing a blog search for R in Google- Revo is now down to number 7 (which is hmm given Google Instant)
Of course I think too much about SEO, but I dont run CPC ads- I made much more money when traffic is low – say 5-10 small businesses needing to forecast their sales .
and enjoy your Thanksgiving. Remember the Indians bring the Turkeys.
Project Titan — a web-based email client that we hear is unofficially referred to internally as its “Gmail killer”. Now we’ve heard from sources that this is indeed what’s coming on Monday during Facebook’s special event, alongside personal @facebook.com email addresses for users.
Now Techcrunch always tells the Truth and the Gospel as per Mike is always right, especially when he is talking of gates of heaven and Angels.
Again as per the newly rich Mike Arringotn (who qualifies to be an Angel Investor himself except AOL has locked in his err wings)
Our understanding is that this is more than just a UI refresh for Facebook’s existing messaging service with POP access tacked on. Rather, Facebook is building a full-fledged webmail client, and while it may only be in early stages come its launch Monday, there’s a huge amount of potential here.
Facebook has the world’s most popular photos product, the most popular events product, and soon will have a very popular local deals product as well. It can tweak the design of its webmail client to display content from each of these in a seamless fashion (and don’t forget messages from games, or payments via Facebook Credits). And there’s also the social element: Facebook knows who your friends are and how closely you’re connected to them; it can probably do a pretty good job figuring out which personal emails you want to read most and prioritize them accordingly.
Oh, and assuming our sources prove accurate, this explains the timing of the Google/Facebook slap fight over contact information.
In an exclusive chat with Decisionstats, Senior VP Eduard Patel Bumberg said- This is it. I am going to kill Gmail. This movie I just had a small part in the mens room while they had the groupies. If we finally kill Gmail, I hope to get a much bigger part in Social Network 3.
New The new Facebook email gives you lesses spam (primarily) as it leans on its contacts in the Cosa Nostra of Spam- and tell them no spam to .fb books.
Yes Anyone is someone in spam has had a connection in the spam pie in Facebook, like creating duplicate 50 million accounts just before the movie got launched, inflating the number of daily Farmville players, invites, links .
Arringutan even covered some of it in an earlier FB game called scamville.
Saint Mark and Mike would have approved Senior VP Eduard Patel Bumberg decision to either kill Gmail or commit hara kari live on U Stream. It is good for the sequel.