Brief Interview with James G Kobielus

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

About –http://www.forrester.com/rb/analyst/james_kobielus

James G. Kobielus
Senior Analyst, Forrester Research

RESEARCH FOCUS

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

Predictive Analytics World March2011 SF

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Message from PAWCON-

 

Predictive Analytics World, Mar 14-15 2011, San Francisco, CA

More info: pawcon.com/sanfrancisco

Agenda at-a-glance: pawcon.com/sanfrancisco/2011/agenda_overview.php

PAW’s San Francisco 2011 program is the richest and most diverse yet, including over 30 sessions across two tracks – an “All Audiences” and an “Expert/Practitioner” track — so you can witness how predictive analytics is applied at Bank of America, Bank of the West, Best Buy, CA State Automobile Association, Cerebellum Capital, Chessmetrics, Fidelity, Gaia Interactive, GE Capital, Google, HealthMedia, Hewlett Packard, ICICI Bank (India), MetLife, Monster.com, Orbitz, PayPal/eBay, Richmond, VA Police Dept, U. of Melbourne, Yahoo!, YMCA, and a major N. American telecom, plus insights from projects for Anheiser-Busch, the SSA, and Netflix.

PAW’s agenda covers hot topics and advanced methods such as uplift modeling (net lift), ensemble models, social data (6 sessions on this), search marketing, crowdsourcing, blackbox trading, fraud detection, risk management, survey analysis, and other innovative applications that benefit organizations in new and creative ways.

Predictive Analytics World is the only conference of its kind, delivering vendor-neutral sessions across verticals such as banking, financial services, e-commerce, education, government, healthcare, high technology, insurance, non-profits, publishing, social gaming, retail and telecommunications

And PAW covers the gamut of commercial applications of predictive analytics, including response modeling, customer retention with churn modeling, product recommendations, fraud detection, online marketing optimization, human resource decision-making, law enforcement, sales forecasting, and credit scoring.

WORKSHOPS. PAW also features pre- and post-conference workshops that complement the core conference program. Workshop agendas include advanced predictive modeling methods, hands-on training and enterprise decision management.

More info: pawcon.com/sanfrancisco

Agenda at-a-glance: pawcon.com/sanfrancisco/2011/agenda_overview.php

Be sure to register by Dec 7 for the Super Early Bird rate (save $400):
pawcon.com/sanfrancisco/register.php

If you’d like our informative event updates, sign up at:
pawcon.com/signup-us.php

Quantifying Analytics ROI

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I had a brief twitter exchange with Jim Davis, Chief Marketing Officer, SAS Institute on Return of Investment on Business Analytics Projects for customers. I have interviewed Jim Davis before last year https://decisionstats.com/2009/06/05/interview-jim-davis-sas-institute/

Now Jim Davis is a big guy, and he is rushing from the launch of SAS Institute’s Social Media Analytics in Japan- to some arguably difficult flying conditions in time to be home in America for Thanksgiving. That and and I have not been much of a good Blog Boy recently, more swayed by love of open source, than love of software per se. I love equally, given I am bad at both equally.

Anyways, Jim’s contention  ( http://twitter.com/Davis_Jim ) was customers should go in business analytics only if there is Positive Return on Investment.  I am quoting him here-

What is important is that there be a positive ROI on each and every BA project. Otherwise don’t do it.

That’s not the marketing I was taught in my business school- basically it was sell, sell, sell.

However I see most BI sales vendors also go through -let me meet my sales quota for this quarter- and quantifying customer ROI is simple maths than predictive analytics but there seems to be some information assymetry in it.

Here is a paper from North Western University on ROI in IT projects-.

but overall it would be in the interest of customers and Business Analytics Vendors to publish aggregated ROI.

The opponents to this transparency in ROI would be market leaders in market share, who have trapped their customers by high migration costs (due to complexity) or contractually.

A recent study listed Oracle having a large percentage of unhappy customers who would still renew!, SAP had problems when it raised prices for licensing arbitrarily (that CEO is now CEO of HP and dodging legal notices from Oracle).

Indeed Jim Davis’s famous unsettling call for focusing on Business Analytics,as Business Intelligence is dead- that call has been implemented more aggressively by IBM in analytical acquisitions than even SAS itself which has been conservative about inorganic growth. Quantifying ROI, should theoretically aid open source software the most (since they are cheapest in up front licensing) or newer technologies like MapReduce /Hadoop (since they are quite so fast)- but I think that market has a way of factoring in these things- and customers are not as foolish neither as unaware of costs versus benefits of migration.

The contrary to this is Business Analytics and Business Intelligence are imperfect markets with duo-poly  or big players thriving in absence of customer regulation.

You get more protection as a customer of $20 bag of potato chips, than as a customer of a $200,000 software. Regulators are wary to step in to ensure ROI fairness (since most bright techies are qither working for private sector, have their own startup or invested in startups)- who in Govt understands Analytics and Intelligence strong enough to ensure vendor lock-ins are not done, and market flexibility is done. It is also a lower choice for embattled regulators to ensure ROI on enterprise software unlike the aggressiveness they have showed in retail or online software.

Who will Analyze the Analysts and who can quantify the value of quants (or penalize them for shoddy quantitative analytics)- is an interesting phenomenon we expect to see more of.

 

 

PAWCON -This week in London

Watch out for the twitter hash news on PAWCON and the exciting agenda lined up. If your in the City- you may want to just drop in

http://www.predictiveanalyticsworld.com/london/2010/agenda.php#day1-7

Disclaimer- PAWCON has been a blog partner with Decisionstats (since the first PAWCON ). It is vendor neutral and features open source as well proprietary software, as well case studies from academia and Industry for a balanced view.

 

Little birdie told me some exciting product enhancements may be in the works including a not yet announced R plugin 😉 and the latest SAS product using embedded analytics and Dr Elder’s full day data mining workshop.

Citation-

http://www.predictiveanalyticsworld.com/london/2010/agenda.php#day1-7

Monday November 15, 2010
All conference sessions take place in Edward 5-7

8:00am-9:00am

Registration, Coffee and Danish
Room: Albert Suites


9:00am-9:50am

Keynote
Five Ways Predictive Analytics Cuts Enterprise Risk

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 will reveal:

  • 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

 

Speaker: Eric Siegel, Ph.D., Program Chair, Predictive Analytics World

Top of this page ] [ Agenda overview ]


IBM9:50am-10:10am

Platinum Sponsor Presentation
The Analytical Revolution

The algorithms at the heart of predictive analytics have been around for years – in some cases for decades. But now, as we see predictive analytics move to the mainstream and become a competitive necessity for organisations in all industries, the most crucial challenges are to ensure that results can be delivered to where they can make a direct impact on outcomes and business performance, and that the application of analytics can be scaled to the most demanding enterprise requirements.

This session will look at the obstacles to successfully applying analysis at the enterprise level, and how today’s approaches and technologies can enable the true “industrialisation” of predictive analytics.

Speaker: Colin Shearer, WW Industry Solutions Leader, IBM UK Ltd

Top of this page ] [ Agenda overview ]


Deloitte10:10am-10:20am

Gold Sponsor Presentation
How Predictive Analytics is Driving Business Value

Organisations are increasingly relying on analytics to make key business decisions. Today, technology advances and the increasing need to realise competitive advantage in the market place are driving predictive analytics from the domain of marketers and tactical one-off exercises to the point where analytics are being embedded within core business processes.

During this session, Richard will share some of the focus areas where Deloitte is driving business transformation through predictive analytics, including Workforce, Brand Equity and Reputational Risk, Customer Insight and Network Analytics.

Speaker: Richard Fayers, Senior Manager, Deloitte Analytical Insight

Top of this page ] [ Agenda overview ]


10:20am-10:45am

Break / Exhibits
Room: Albert Suites


10:45am-11:35am
Healthcare
Case Study: Life Line Screening
Taking CRM Global Through Predictive Analytics

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, Life Line Screening

Top of this page ] [ Agenda overview ]


11:35am-12:25pm
Open Source Analytics; Healthcare
Case Study: A large health care organization
The Rise of Open Source Analytics: Lowering Costs While Improving Patient Care

Rapidminer and R were the number 1 and 2 in this years annual KDNuggets data mining tool usage poll, followed by Knime on place 4 and Weka on place 6. So what’s going on here? Are these open source tools really that good or is their popularity strongly correlated with lower acquisition costs alone? This session answers these questions based on a real world case for a large health care organization and explains the risks & benefits of using open source technology. The final part of the session explains how these tools stack up against their traditional, proprietary counterparts.

Speaker: Jos van Dongen, Associate & Principal, DeltIQ Group

Top of this page ] [ Agenda overview ]


12:25pm-1:25pm

Lunch / Exhibits
Room: Albert Suites


1:25pm-2:15pm
Keynote
Thought Leader:
Case Study: Yahoo! and other large on-line e-businesses
Search Marketing and Predictive Analytics: SEM, SEO and On-line Marketing Case Studies

Search Engine Marketing is a $15B industry in the U.S. growing to double that number over the next 3 years. Worldwide the SEM market was over $50B in 2010. Not only is this a fast growing area of marketing, but it is one that has significant implications for brand and direct marketing and is undergoing rapid change with emerging channels such as mobile and social. What is unique about this area of marketing is a singularly heavy dependence on analytics:

 

  • Large numbers of variables and options
  • Real-time auctions/bids and a need to adjust strategies in real-time
  • Difficult optimization problems on allocating spend across a huge number of keywords
  • Fast-changing competitive terrain and heavy competition on the obvious channels
  • Complicated interactions between various channels and a large choice of search keyword expansion possibilities
  • Profitability and ROI analysis that are complex and often challenging

 

The size of the industry, its growing importance in marketing, its upcoming role in Mobile Advertising, and its uniquely heavy reliance on analytics makes it particularly interesting as an area for predictive analytics applications. In this session, not only will hear about some of the latest strategies and techniques to optimize search, you will hear case studies that illustrate the important role of analytics from industry practitioners.

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

Top of this page ] [ Agenda overview ]


SAS2:15pm-2:35pm

Platinum Sponsor Presentation
Creating a Model Factory Using in-Database Analytics

With the ever-increasing number of analytical models required to make fact-based decisions, as well as increasing audit compliance regulations, it is more important than ever that these models can be created, monitored, retuned and deployed as quickly and automatically as possible. This paper, using a case study from a major financial organisation, will show how organisations can build a model factory efficiently using the latest SAS technology that utilizes the power of in-database processing.

Speaker: John Spooner, Analytics Specialist, SAS (UK)

Top of this page ] [ Agenda overview ]


2:35pm-2:45pm

Session Break
Room: Albert Suites


2:45pm-3:35pm

Retail
Case Study: SABMiller
Predictive Analytics & Global Marketing Strategy

Over the last few years SABMiller plc, the second largest brewing company in the world operating in 70 countries, has been systematically segmenting its markets in different countries globally in order optimize their portfolio strategy & align it to their long term country specific growth strategy. This presentation talks about the overall methodology followed and the challenges that had to be overcome both from a technical as well as from a change management stand point in order to successfully implement a standard analytics approach to diverse markets and diverse business positions in a highly global setting.

The session explains how country specific growth strategies were converted to objective variables and consumption occasion segments were created that differentiated the market effectively by their growth potential. In addition to this the presentation will also provide a discussion on issues like:

  • The dilemmas of static vs. dynamic solutions and standardization vs. adaptable solutions
  • Challenges in acceptability, local capability development, overcoming implementation inertia, cost effectiveness, etc
  • The role that business partners at SAB and analytics service partners at AbsolutData together play in providing impactful and actionable solutions

 

Speaker: Anne Stephens, SABMiller plc

Speaker: Titir Pal, AbsolutData

Top of this page ] [ Agenda overview ]


3:35pm-4:25pm

Retail
Case Study: Overtoom Belgium
Increasing Marketing Relevance Through Personalized Targeting

 

Since many years, Overtoom Belgium – a leading B2B retailer and division of the French Manutan group – focuses on an extensive use of CRM. In this presentation, we demonstrate how Overtoom has integrated Predictive Analytics to optimize customer relationships. In this process, they employ analytics to develop answers to the key question: “which product should we offer to which customer via which channel”. We show how Overtoom gained a 10% revenue increase by replacing the existing segmentation scheme with accurate predictive response models. Additionally, we illustrate how Overtoom succeeds to deliver more relevant communications by offering personalized promotional content to every single customer, and how these personalized offers positively impact Overtoom’s conversion rates.

Speaker: Dr. Geert Verstraeten, Python Predictions

Top of this page ] [ Agenda overview ]


4:25pm-4:50pm

Break / Exhibits
Room: Albert Suites


4:50pm-5:40pm
Uplift Modelling:
Case Study: Lloyds TSB General Insurance & US Bank
Uplift Modelling: You Should Not Only Measure But Model Incremental Response

Most marketing analysts understand that measuring the impact of a marketing campaign requires a valid control group so that uplift (incremental response) can be reported. However, it is much less widely understood that the targeting models used almost everywhere do not attempt to optimize that incremental measure. That requires an uplift model.

This session will explain why a switch to uplift modelling is needed, illustrate what can and does go wrong when they are not used and the hugely positive impact they can have when used effectively. It will also discuss a range of approaches to building and assessing uplift models, from simple basic adjustments to existing modelling processes through to full-blown uplift modelling.

The talk will use Lloyds TSB General Insurance & US Bank as a case study and also illustrate real-world results from other companies and sectors.

 

Speaker: Nicholas Radcliffe, Founder and Director, Stochastic Solutions

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5:40pm-6:30pm

Consumer services
Case Study: Canadian Automobile Association and other B2C examples
The Diminishing Marginal Returns of Variable Creation in Predictive Analytics Solutions

 

Variable Creation is the key to success in any predictive analytics exercise. Many different approaches are adopted during this process, yet there are diminishing marginal returns as the number of variables increase. Our organization conducted a case study on four existing clients to explore this so-called diminishing impact of variable creation on predictive analytics solutions. Existing predictive analytics solutions were built using our traditional variable creation process. Yet, presuming that we could exponentially increase the number of variables, we wanted to determine if this added significant benefit to the existing solution.

Speaker: Richard Boire, BoireFillerGroup

Top of this page ] [ Agenda overview ]


6:30pm-7:30pm

Reception / Exhibits
Room: Albert Suites


Tuesday November 16, 2010
All conference sessions take place in Edward 5-7

8:00am-9:00am

Registration, Coffee and Danish
Room: Albert Suites


9:00am-9:55am
Keynote
Multiple Case Studies: Anheuser-Busch, Disney, HP, HSBC, Pfizer, and others
The High ROI of Data Mining for Innovative Organizations

Data mining and advanced analytics can enhance your bottom line in three basic ways, by 1) streamlining a process, 2) eliminating the bad, or 3) highlighting the good. In rare situations, a fourth way – creating something new – is possible. But modern organizations are so effective at their core tasks that data mining usually results in an iterative, rather than transformative, improvement. Still, the impact can be dramatic.

Dr. Elder will share the story (problem, solution, and effect) of nine projects conducted over the last decade for some of America’s most innovative agencies and corporations:

    Streamline:

  • Cross-selling for HSBC
  • Image recognition for Anheuser-Busch
  • Biometric identification for Lumidigm (for Disney)
  • Optimal decisioning for Peregrine Systems (now part of Hewlett-Packard)
  • Quick decisions for the Social Security Administration
    Eliminate Bad:

  • Tax fraud detection for the IRS
  • Warranty Fraud detection for Hewlett-Packard
    Highlight Good:

  • Sector trading for WestWind Foundation
  • Drug efficacy discovery for Pharmacia & UpJohn (now Pfizer)

Moderator: Eric Siegel, Program Chair, Predictive Analytics World

Speaker: John Elder, Ph.D., Elder Research, Inc.

Also see Dr. Elder’s full-day workshop

 

Top of this page ] [ Agenda overview ]


9:55am-10:30am

Break / Exhibits
Room: Albert Suites


10:30am-11:20am
Telecommunications
Case Study: Leading Telecommunications Operator
Predictive Analytics and Efficient Fact-based Marketing

The presentation describes what are the major topics and issues when you introduce predictive analytics and how to build a Fact-Based marketing environment. The introduced tools and methodologies proved to be highly efficient in terms of improving the overall direct marketing activity and customer contact operations for the involved companies. Generally, the introduced approaches have great potential for organizations with large customer bases like Mobile Operators, Internet Giants, Media Companies, or Retail Chains.

Main Introduced Solutions:-Automated Serial Production of Predictive Models for Campaign Targeting-Automated Campaign Measurements and Tracking Solutions-Precise Product Added Value Evaluation.

Speaker: Tamer Keshi, Ph.D., Long-term contractor, T-Mobile

Speaker: Beata Kovacs, International Head of CRM Solutions, Deutsche Telekom

Top of this page ] [ Agenda overview ]


11:20am-11:25am

Session Changeover


11:25am-12:15pm
Thought Leader
Nine Laws of Data Mining

Data mining is the predictive core of predictive analytics, a business process that finds useful patterns in data through the use of business knowledge. The industry standard CRISP-DM methodology describes the process, but does not explain why the process takes the form that it does. I present nine “laws of data mining”, useful maxims for data miners, with explanations that reveal the reasons behind the surface properties of the data mining process. The nine laws have implications for predictive analytics applications: how and why it works so well, which ambitions could succeed, and which must fail.

 

Speaker: Tom Khabaza, khabaza.com

 

Top of this page ] [ Agenda overview ]


12:15pm-1:30pm

Lunch / Exhibits
Room: Albert Suites


1:30pm-2:25pm
Expert Panel: Kaboom! Predictive Analytics Hits the Mainstream

Predictive analytics has taken off, across industry sectors and across applications in marketing, fraud detection, credit scoring and beyond. Where exactly are we in the process of crossing the chasm toward pervasive deployment, and how can we ensure progress keeps up the pace and stays on target?

This expert panel will address:

  • How much of predictive analytics’ potential has been fully realized?
  • Where are the outstanding opportunities with greatest potential?
  • What are the greatest challenges faced by the industry in achieving wide scale adoption?
  • How are these challenges best overcome?

 

Panelist: John Elder, Ph.D., Elder Research, Inc.

Panelist: Colin Shearer, WW Industry Solutions Leader, IBM UK Ltd

Panelist: Udo Sglavo, Global Analytic Solutions Manager, SAS

Panel moderator: Eric Siegel, Ph.D., Program Chair, Predictive Analytics World


2:25pm-2:30pm

Session Changeover


2:30pm-3:20pm
Crowdsourcing Data Mining
Case Study: University of Melbourne, Chessmetrics
Prediction Competitions: Far More Than Just a Bit of Fun

Data modelling competitions allow companies and researchers to post a problem and have it scrutinised by the world’s best data scientists. There are an infinite number of techniques that can be applied to any modelling task but it is impossible to know at the outset which will be most effective. By exposing the problem to a wide audience, competitions are a cost effective way to reach the frontier of what is possible from a given dataset. The power of competitions is neatly illustrated by the results of a recent bioinformatics competition hosted by Kaggle. It required participants to pick markers in HIV’s genetic sequence that coincide with changes in the severity of infection. Within a week and a half, the best entry had already outdone the best methods in the scientific literature. This presentation will cover how competitions typically work, some case studies and the types of business modelling challenges that the Kaggle platform can address.

Speaker: Anthony Goldbloom, Kaggle Pty Ltd

Top of this page ] [ Agenda overview ]


3:20pm-3:50pm

Breaks /Exhibits
Room: Albert Suites


3:50pm-4:40pm
Human Resources; e-Commerce
Case Study: Naukri.com, Jeevansathi.com
Increasing Marketing ROI and Efficiency of Candidate-Search with Predictive Analytics

InfoEdge, India’s largest and most profitable online firm with a bouquet of internet properties has been Google’s biggest customer in India. Our team used predictive modeling to double our profits across multiple fronts. For Naukri.com, India’s number 1 job portal, predictive models target jobseekers most relevant to the recruiter. Analytical insights provided a deeper understanding of recruiter behaviour and informed a redesign of this product’s recruiter search functionality. This session will describe how we did it, and also reveal how Jeevansathi.com, India’s 2nd-largest matrimony portal, targets the acquisition of consumers in the market for marriage.

 

Speaker: Suvomoy Sarkar, Chief Analytics Officer, HT Media & Info Edge India (parent company of the two companies above)

 

Top of this page ] [ Agenda overview ]


4:40pm-5:00pm
Closing Remarks

Speaker: Eric Siegel, Ph.D., Program Chair, Predictive Analytics World

Top of this page ] [ Agenda overview ]


Wednesday November 17, 2010

Full-day Workshop
The Best and the Worst of Predictive Analytics:
Predictive Modeling Methods and Common Data Mining Mistakes

Click here for the detailed workshop description

  • Workshop starts at 9:00am
  • First AM Break from 10:00 – 10:15
  • Second AM Break from 11:15 – 11:30
  • Lunch from 12:30 – 1:15pm
  • First PM Break: 2:00 – 2:15
  • Second PM Break: 3:15 – 3:30
  • Workshop ends at 4:30pm

Speaker: John Elder, Ph.D., CEO and Founder, Elder Research, Inc.

 

SAS for Job Interviews

SAS Institute, Solutions
Image via Wikipedia

Yeah. I hope someone wrote a book like that.

Basically,

  1. Libname
  2. Proc Datasets
  3. Proc Import
  4. Proc Contents
  5. Proc Freq
  6. Proc Means
  7. Proc Univariate
  8. Proc Reg
  9. Proc Logistic
  10. Proc Export (to excel where you do the graphs)
  11. ODS
  12. Proc Tabulate

(note – it would be interesting to do a proc freq on all procs say used say on SAS On Demand)

Any thing else is not needed for a entry level job for a fresh grad student or job for a veteran re-trained worker.

Just like society needs science and commerce as twin pillars, analytics needs SAS (great Marketing) and R (great research) for expanding the pie of analytics which is woefully underutilized and stupidly overcapitalized by jazzy-copy-paste-data-from-query- software disguised as “intelligent software”.  R has no certification and no formal training for jobs (as yet) though this should change. SAS looks great (still) for getting jobs for grad students. R looks great (yup) for getting research jobs probably not corporate analytics jobs ?What do you think?

 

Scoring SAS and SPSS Models in the cloud

Outline of a cloud containing text 'The Cloud'
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An announcement from Zementis and Predixion Software– about using cloud computing for scoring models using PMML. Note R has a PMML package as well which is used by Rattle, data mining GUI for exporting models.

Source- http://www.marketwatch.com/story/predixion-software-introduces-new-product-to-run-sas-and-spss-predictive-models-in-the-cloud-2010-10-19?reflink=MW_news_stmp

——————————————————————————————————–

ALISO VIEJO, Calif., Oct 19, 2010 (BUSINESS WIRE) — Predixion Software today introduced Predixion PMML Connexion(TM), an interface that provides Predixion Insight(TM), the company’s low-cost, self-service in the cloud predictive analytics solution, direct and seamless access to SAS, SPSS (IBM) and other predictive models for use by Predixion Insight customers. Predixion PMML Connexion enables companies to leverage their significant investments in legacy predictive analytics solutions at a fraction of the cost of conventional licensing and maintenance fees.

The announcement was made at the Predictive Analytics World conference in Washington, D.C. where Predixion also announced a strategic partnership with Zementis, Inc., a market leader in PMML-based solutions. Zementis is exhibiting in Booth #P2.

The Predictive Model Markup Language (PMML) standard allows for true interoperability, offering a mature standard for moving predictive models seamlessly between platforms. Predixion has fully integrated this PMML functionality into Predixion Insight, meaning Predixion Insight users can now effortlessly import PMML-based predictive models, enabling information workers to score the models in the cloud from anywhere and publish reports using Microsoft Excel(R) and SharePoint(R). In addition, models can also be written back into SAS, SPSS and other platforms for a truly collaborative, interoperable solution.

“Predixion’s investment in this PMML interface makes perfect business sense as the lion’s share of the models in existence today are created by the SAS and SPSS platforms, creating compelling opportunity to leverage existing investments in predictive and statistical models on a low-cost cloud predictive analytics platform that can be fed with enterprise, line of business and cloud-based data,” said Mike Ferguson, CEO of Intelligent Business Strategies, a leading analyst and consulting firm specializing in the areas of business intelligence and enterprise business integration. “In this economy, Predixion’s low-cost, self-service predictive analytics solutions might be welcome relief to IT organizations chartered with quickly adding additional applications while at the same time cutting costs and staffing.”

“We are pleased to be partnering with Zementis, truly a PMML market leader and innovator,” said Predixion CEO Simon Arkell. “To allow any SAS or SPSS customer to immediately score any of their predictive models in the cloud from within Predixion Insight, compare those models to those created by Predixion Insight, and share the results within Excel and Sharepoint is an exciting step forward for the industry. SAS and SPSS customers are fed up with the high prices they must pay for their business users just to access reports generated by highly skilled PhDs who are burdened by performing routine tasks and thus have become a massive bottleneck. That frustration is now a thing of the past because any information worker can now unlock the power of predictive analytics without relying on experts — for a fraction of the cost and from anywhere they can connect to the cloud,” Arkell said.

Dr. Michael Zeller, Zementis CEO, added, “Our mission is to significantly shorten the time-to-market for predictive models in any industry. We are excited to be contributing to Predixion’s self-service, cloud-based predictive analytics solution set.”

About Predixion Software

Predixion Software develops and markets collaborative predictive analytics solutions in the public and private cloud. Predixion enables self-service predictive analytics, allowing customers to use and analyze large amounts of data to make actionable decisions, all within the familiar environment of Excel and PowerPivot. Predixion customers are achieving immediate results across a multitude of industries including: retail, finance, healthcare, marketing, telecommunications and insurance/risk management.

Predixion Software is headquartered in Aliso Viejo, California with development offices in Redmond, Washington. The company has venture capital backing from established investors including DFJ Frontier, Miramar Venture Partners and Palomar Ventures. For more information please contact us at 949-330-6540, or visit us atwww.predixionsoftware.com.

About Zementis

Zementis, Inc. is a leading software company focused on the operational deployment and integration of predictive analytics and data mining solutions. Its ADAPA(R) decision engine successfully bridges the gap between science and engineering. ADAPA(R) was designed from the ground up to benefit from open standards and to significantly shorten the time-to-market for predictive models in any industry. For more information, please visit www.zementis.com.

 

Bruno Aziza, Microsoft Global BI Lead joins PAW Keynote

By Richard Wheeler (Zephyris) 2007. Lambda rep...
Image via Wikipedia

 

An interesting development, Bruno Aziza, Director, Worldwide Strategy Lead, Business Intelligence, Microsoft has joined Predictive Analytics World as a keynote speaker.

http://www.predictiveanalyticsworld.com/dc/2010/agenda.php#day2-2

Keynote
Predictive Analytics and Business Performance

In this session, Bruno Aziza will discuss the challenges organizations face with Analytics and Performance. This participative session will provide first-hand accounts from Fortune 500 companies who are winning by building accountability, intelligence, and informed decision-making into their organizational DNA.

Speaker: Bruno Aziza, Director, Worldwide Strategy Lead, Business Intelligence, Microsoft

Some info about Mr Aziza,

http://www.predictiveanalyticsworld.com/dc/2010/speakers.php#aziza

Bruno Aziza, Director, Worldwide Strategy Lead, Business Intelligence,Microsoft

Bruno AzizaBruno Aziza is a recognized authority on Strategy Execution, Business Intelligence and Information Management. He is the co-author of best-selling book, “Drive Business Performance: Enabling a Culture of Intelligent Execution” and a Fellow at the Advanced Performance Institute, a world-leading and independent advisory group specialized in organizational performance. Drs. Kaplan & Norton, of Balanced Scorecard fame, praise Aziza for moving “the field of performance management forward in important new directions.”

Aziza’s work has been featured in publications across North America, Europe and Asia such as Business Finance magazine, Intelligent Enterprise, CRM magazine and others.

Aziza has held management positions at Apple Inc.Business Objects (SAP), AppStream(Symantec) and Decathlon SA. He currently works on Microsoft Business Intelligence go-to-market strategy and execution for partners, services, sales and marketing. Aziza lives in Seattle with his family and enjoys sports and travelling.

He regularly provides views on leadership and performance on the SuccessFactors thought leader Network , the CIO Network and Forbes Magazine. Aziza is the host ofBizIntelligence.TV – a leading weekly show on Business Intelligence and Analytics. An award-winning speaker, Aziza frequently keynotes international events and has shared the stage with executives and thought leaders such as Dr. Kaplan. Aziza’s biggest crowd to date is 5,000 people.

Follow or contact Bruno via:
•Twitter @ http://twitter.com/brunoaziza
•Facebook @ http://tinyurl.com/bruno-on-facebook
•Linkedin @ http://www.linkedin.com/in/brunoaziza
•YouTube @ http://tinyurl.com/bruno-on-tv
•Kindle blog @ http://tinyurl.com/culture-blog
•Forbes blog @ http://tinyurl.com/culture-blog

That makes it an interesting Pow Wow between the big players at the conference Oracle,SAP, IBM, SAS and now MS –all seem to be there.

Truly a Predictive Analytics World.