may the best customer experience win. with the foresee’s patented customer experience technology,...

PRODUCED BY:

www.predictiveanalyticsworld.com/sanfrancisco

April 14 - April 19, 2013 ● San Francisco

CONFERENCE GUIDE

KEYNOTE SPEAKERS

Plus a special plenary sessionfrom industry heavy-weight:

Rayid GhaniChief Data ScientistObama for America

Anthony Goldbloom CEOKaggle

EdwardNazarko Client Technical AdvisorIBM

Dr. John ElderCEO & FounderElder Research, Inc.

DIAMOND SPONSORS

DDBWSF2013

PW: ddbwsf13

MAY THE BESTCUSTOMER

EXPERIENCE WIN.

www.foresee.com

With the ForeSee’s patented Customer Experience technology, you can precisely measure the experience, acquirecustomer intelligence, analyze the data and take action.

The results are better experiences for consumers and a better business for you.

Visit ForeSee at Booth 301

© 2013 ForeSee. All rights reserved.

© 2013 Rising Media, Inc. 1 www.predictiveanalyticsworld.com/sanfrancisco

Welcome

Table of ContentsAgenda Overview ..........................2

Conference Floorplan ..................9

Session Descriptions ....................10

Workshop Descriptions ..............26

Speaker & Keynote Bios ..............35

Exhibitor Floorplan .....................36

Sponsors .......................................37

Sponsor Profiles ...........................38

Predictive Analytics World Stay Engaged

Connect with your peers, the latest conference news and more on social media:

Twitter: @PAWConConference Hashtag #PAWConFacebook: facebook.com/PAWConLinkedIn Group: Predictive Analytics World

Conference Attendees Will Receive a free copy of PAW Founder Eric Siegel’s Book:

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die

Welcome to Predictive Analytics World!You have come to the leading business event, loaded with predictive analytics case studies, expertise and resources. This conference brings professionals and experts together to keep predictive analytics on a forward trajectory, strengthening the impact delivered and establishing new opportunities.

PAW is a part of Data Driven Business Week. This multi-conference “überevent” spans topics in analytics and beyond, reflecting the growing importance and visibility of the industry. You benefit from this cross-pollination by access to cross conference expositions, shared workshops, and cross-registration options.

Each of the millions of business decisions driven by analytics are based on concrete evidence and sound mathematics. That is truly an upgrade to the way we do business. And everywhere you turn, this upgrade is “installed” in new, innovative ways by driving different types of operational decisions with the scores produced by predictive models. PAW’s extensive array of case studies prove that these innovations deliver.

Enjoy, take advantage, and have a great conference!

Regards,

Eric Siegel, Ph.D.Founder & Program ChairPredictive Analytics World


Agenda Overview

l FOR All lEvElS s FOR ExPERT/PRACTITIOnERS

Pre-Conference Workshop: Sunday, April 14, 2013

Full-DAy WORkShOP l

R for Predictive Modeling: A Hands-On Introduction • Room: Salon 5 & 6 Max Kuhn, Director, Pfizer

Day 1: Monday, April 15, 2013

8:00-9:00am Registration & Networking Breakfast • Room: Foyer

9:00-9:05amConference Chair Welcome Remarks • Room: Golden Gate A

Eric Siegel, Ph.D., Predictive Analytics World

9:05-9:20am

Diamond Sponsor Presentation • Room: Golden Gate AMeasure Right, Manage Forward, Make a Difference

Eric Feinberg, ForeSee

9:20-10:10am

keynote

The $3m Heritage Health Prize: Results and Conclusions • Room: Golden Gate A

Anthony Goldbloom, Kaggle

10:10-10:40am Exhibits & Morning Coffee Break • Room: Exhibit Hall

Track 1: All levelsRoom: Salon 5 & 6

Track 2: Expert/PractitionersRoom: Golden Gate A

10:40-10:50am

Gold Sponsor Presentation

The Future of Commerce is HereAlok Bhanot, Inkiru, Inc.


Application of Innovative Analytics in Business

Guha Athreya, AbsolutData

10:50-11:35am

Social Data Financial Services

Mapping Social Media to Predict Influence and Measure Propagation l Marc Smith, Social Media Research Foundation

Case Study: Scotiabank s

Mortgage Liquidation Model Building and Application

Jane Zhong, Scotiabank

Wenlei Shi, Scotiabank




11:40am-12:00pm

Survey Analysis uplift Modeling

Case Study: Cox Communications l

Using Analytics to Guide the Creation of Creative for Segment-Targeted

Campaigns Bob Wood, Merkle

Case Study: Intuit s

Uplift Modeling - Direct Marketing Case Studies

Madhu Iyer, Intuit

Inna Shapotina, Intuit

12:05-12:25pm

Spam Detection uplift Modeling

Case Study: MailChimp.com l

Monkeys & Math: How MailChimp Catches Bad Guys

John Foreman, MailChimp.com

Case Study: Hewlett-Packard s

A Generic Uplift Modeling Framework to Calculate ROI - Application in

Promotion EffectivenessJyotirmay nag, Hewlett-Packard

12:25-1:30pm lunch • Room: Exhibit Hall

lunch & learn • Room: Golden Gate A

Industrialization of Analytics – Enjoy the Journey

Pankaj Kulshreshtha, Genpact

David Kreutter, Pfizer

1:30-2:15pm

keynote • Room: Golden Gate A

Analytics and the Presidential Elections

Rayid Ghani, Obama for America

2:15-2:30pm

Vendor Elevator Pitches • Room: Golden Gate A


Agenda Overview




2:35-2:55pm

eCommerce Analytics Advanced Methods

Case Study: Minted.com l

Mining Customer Behavior for Targeted Marketing

Jim Porzak, Minted

Anne-Elise lansdown, MintedCase Study: Qualcomm s

M.A.R.S. - an Underused Modeling Method

Maria lupetini, Qualcomm Technologies

3:00-3:20pm

Analytics Team Building & Management

Case Study: Netflix l

Building a Data Science Team from Scratch

Chris Pouliot, netflix

3:20-3:50pm Exhibits & Afternoon Break • Room: Exhibit Hall

3:50-4:10pm

Search Engine Marketing Insurance / Fraud Detection

Case Study: Kelley Blue Book l

Driving Search Engine Marketing with Deep Analytics

Shawn Hushman, Kelley Blue BookCase Study: Selective Insurance Group s

Strategies and Considerations for Fraud Detection in Insurance Claims

Bob Biermann, Selective Insurance Group

4:15-4:35pm

Budgeting & Macroeconomics

Case Study: Hewlett-Packard l

An Innovative Approach to Hedge Against Macroeconomic

Uncertainties Affecting BusinessesSrinidhi Srinivasan, Hewlett-Packard

Keshav loomb, Hewlett-PackardAshish Kumar Singh, Hewlett-Packard

Agenda Overview





4:40-5:25pm

Industry Skills Insurance

Case Study: Orbitz l

Delivering on Expectations: Core Competencies for Data Scientists

Sameer Chopra, Orbitz WorldwideWenqing lu, Orbitz Worldwide

Case Study: Broadspire s

To Sue or Not to Sue: Predicting Litigation Risk

Gary Anderberg, Broadspire Bangalore Gunashakar, Broadspire

Sergo Grigalashvili, Crawford & Company

5:30-7:00pm Networking Reception • Room: Exhibit Hall

7:00-10:00pmBay Area SAS users Group Meeting

Room: Golden Gate A

Bay Area useR Group MeetingRoom: Golden Gate B

Day 2: Tuesday, April 16, 2013

8:00-9:00am Registration & Networking Breakfast • Room: Foyer

9:00-9:05amConference Chair Welcome Remarks • Room: Golden Gate A

Eric Siegel, Ph.D., Predictive Analytics World

9:05-9:20am

Diamond Sponsor Presentation • Room: Golden Gate A

Transform Your Future with Predictive AnalyticsJohn MacGregor, SAP

9:20-10:10amkeynote

Putting IBM Watson to Work • Room: Golden Gate A Edward nazarko, IBM

10:10-10:40am Exhibits & Morning Coffee Break • Room: Exhibit Hall



10:40-10:50am Gold Sponsor Presentation


Applying Predictive Analytics in Real-timeJaya Kolhatkar, Inkiru, Inc

Agenda Overview





10:50-11:10am

Industry News Thought leadership

Using Analytics to Build Your Analytics Bench: Announcing 2012 Analytics Professionals

Study Results lGreta Roberts, International

Institute for Analytics

My Five Predictive Analytics Pet Peeves s

Dean Abbott, Abbott Analytics, Inc.

11:15-11:35am

Cross-Enterprise Analytics Next Best Offer

Case Study: Monster Worldwide l

Win With Advanced AnalyticsJean-Paul Isson, Monster Worldwide

Case Study: Hewlett-Packard & WB Mason s

Predicting Next Most likely Supplies Purchase Using Multinomial Logit Avinash Parthasarathy, Hewlett-Packard

Arpit Jain, Hewlett-Packard

Pallavi Gupta Bhowmick, Hewlett-Packard

11:40am-12:00pm

lead Management Brand Analytics

Case Study: Citrix l

How Predictive Analytics Changes the Game by Front-Ending the Funnel

Eva Tsai, Citrix

Case Study: Dell s

The Illusive Brand: How to Measure Brand and the

Communications Focused On Itnatalie Kortum, Dell

12:05-12:25pm

Churn Modeling

Case Study: Paychex l

Customer Retention: Pulling the Needle from the Haystack

Frank Fiorille, Paychex, Inc.

12:25-1:30pm lunch • Room: Exhibit Hall

1:30-1:50pm

Platinum Sponsor Presentation • Room: Golden Gate A

Predicting a Fraudulent Payment – Is it Possible?

Josh Ellis, Deloitte Financial Advisory, Services llP

Agenda Overview



1:50-2:35pm

Special Plenary Session • Room: Golden Gate A

General Lessons We Can Learn from Blackbox Trading

Dr. John Elder, Elder Research, Inc.

2:40-3:25pm

Expert Panel • Room: Golden Gate A

Big Data for Predictive Analytics

Moderator: Eric Siegel, Ph.D., Predictive Analytics World

Panelists: Satish lalchand, Deloitte Financial Advisory Services llP

Anil Kaul, AbsolutData

3:25-3:50pm Exhibits & Afternoon Break • Room: Exhibit Hall



3:50-4:10pm

Data Visualization likelihood-to-Recommend

Case Study: Wells Fargo l

Data Visualization Design Using Shneiderman’s Mantra:

Overview First, Zoom and Filter, Then Details-On-Demand

Eric legrand, Wells Fargo

Dana Zuber, Wells Fargo

Case Study: AAA s

Multicollinearity and Sparse Data in Key Driver Analysis:

Challenges and Solutionsnoe Tuason, AAA-nCnU

Raymond Reno, Market Strategies International

4:15-4:35pm

Insurance & hR Analytics

Case Study: Crawford Global Technical Services s

Using Predictive Analytics for Strategic Planning at Crawford GTSSergo Grigalashvili, Crawford & Company

Dr. Andries Willemse, Crawford & Company

4:40-5:30pm

Data Visualization hR Analytics

Case Study: Blue Shield of California l

No Country for Fat Men - Investigating Obesity with

Visual Analytics

Aaron lai, Blue Shield of California

Case Study: ConAgra Foods s

Aging of the Baby Boomer Generation and the Upcoming Talent Tsunami

KC Bradley, ConAgra Foods

Sara Roberts, ConAgra Foods

Agenda Overview



Post-Conference Workshops

Tuesday, April 16, 2013

Full-DAy WORkShOP l

Making Text Mining Work:Practical Methods and Solutions

Room: Foothill E

Dr. Andrew Fast, Elder Research Inc.

ThREE hOuR WORkShOP l

Mapping Groups of People and What They are Talking About in Social Media

Room: Foothill E

Marc A. Smith, Connected Action Consulting Group

Wednesday, April 17, 2013

Full-DAy WORkShOP l

Supercharging Prediction: Hands-On with Ensemble Models

Room: Pacific J

Dean Abbott, Abbott Analytics, Inc.

Workshop Sponsored by:

Full-DAy WORkShOP l

The Best and the Worst of Predictive Analytics: Predictive Modeling Methods and

Common Data Mining Mistakes Room: Pacific H

Dr. John Elder, Elder Research, Inc

Thursday, April 18, 2013

Full-DAy WORkShOP l

Advanced Methods Hands-on: Predictive Modeling Techniques Room: Pacific B

Dean Abbott, Abbott Analytics

Workshop Sponsored by:

Friday, April 19 and Saturday, April 20, 2013

ONE AND A hAlF DAy WORkShOP l

Net Lift Models: Optimizing the Impact of Your Marketing Room: Foothill D

Kim larsen, MarketShare



Conference Floorplan

Exhibit Hall – Breaks – Lunch

SALON 1 & 2

SALON 3 & 4

SALON 5 & 6

SALON 15

SALON 14

SALON 13

SALONS 10-12

SALON 9

SALON 8

SALON 7

NOB HILLC & D

NOB HILLA & B

GOLDEN GATEBALLROOM B GOLDEN GATE

BALLROOM C2

GOLDEN GATEBALLROOM C3

GOLDEN GATEBALLROOM C1

GOLDEN GATEBALLROOM A

Speaker Registration

SponsorRegistration

AttendeeRegistration

WAL

NU

TRO

OM

LAURELROOM

JUNIPERROOM

Golden GatePre-function Area

Elevators

Elevators

Exhibit Hall

Speaker Registration

FOOTHILLD

FOOTHILLA

FOO

THILL

JFOOTHILL

I

CLUB ROOM

FOOTHILLE

FOOTHILLF

FOOTHILLG1

FOOTHILLG2

FOOTHILLH

ATRIUM LOBBY Resturant


Conference Day 1Monday, April 15, 2013

8:00-9:00am • Room: Foyer

Registration & Networking Breakfast

9:00-9:05am • Room: Golden Gate A

Conference Chair Welcome Remarks

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


Diamond Sponsor Presentation

Measure Right, Manage Forward, Make a DifferenceModern consumers are everywhere, all of the time. As this new generation of customer continues to evolve, so must the analytics used to measure the experiences they have with companies and organizations. Eric Feinberg, Senior Director at ForeSee, will discuss next Generation Customer Experience Analytics as a system of metrics that goes beyond single-number measurements and eliminates outdated metric silos to better support today’s multi-channel, multi-device world we live in. He will explain what this new generation of predictive analytics needs to be and how it can help you create an analytics platform that allows you to measure right, manage forward, and make a difference in your business.

Speaker: Eric Feinberg, Senior Director of Mobile, Media & Entertainment, ForeSee


keynote

The $3m heritage health Prize: Results and ConclusionsThe Heritage Health Prize is the largest ever predictive modeling competition. It required data scientists to build algorithms that predict who will go to hospital in the next year, so that preventive action can be taken. Two years on the prize has now just ended. This talk will talk about the competition and some of the lessons that can be learned from it.

Speaker: Anthony Goldbloom, CEO, Kaggle

10:10-10:40am • Room: Exhibit Hall

Exhibits & Morning Coffee Break

Session DescriptionsMonday, April 15, 2013


www.revolutionanalytics.com/bigdata

What are you waiting for?It’s time to start your own Big Data Revolution.

Open Sourceto the Enterprise

Revolution Analytics Brings

RGet the performance and scalability you need to

deploy predictive models with Big Data.

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10:40-10:50am • Room Salon 5 & 6


The Future of Commerce is hereRetailers are using real-time predictive analytics to drive profitability through top line growth and bottom line cost reduction by assimilating data from across the enterprise and blending that with real-time transactional data to personalize every customer interaction. learn how the Inkiru Predictive Intelligence™ Platform provides an end-to-end solution for data scientists.

Speaker: Alok Bhanot, Founder & CEO, Inkiru, Inc



Application of Innovative Analytics in Business“71% of CMOs feel unprepared to deal with the data explosion over the next five years. 68% feel unprepared to deal with social media. 65% feel unprepared to deal with the growing number of channel and tech device choices.” - InformationWeek

During the session, we will showcase innovations in business applications of analytics designed to guide CxOs to deal with the increasingly complex customer environment

Speaker: Guha Athreya, Sr. Manager, Customer Analytics, AbsolutData

10:50-11:35am • Room: Salon 5 & 6

Track 1: Social Data l

Mapping Social Media to Predict Influence and Measure PropagationHidden within social media streams are structures that identify the most influential voices on any topic. Social network analysis and visualization can take millions of messages and reveal the shape of the crowd and the people at the center of it. Using the free and open nodexl application, this talk demonstrates the tools and methods needed to create detailed maps of any social media topic. learn to map and analyze social networks extracted from email, Facebook, Twitter, YouTube, message boards, and the WWW. no coding or prior experience needed!

Speaker: Marc Smith, Director, Social Media Research Foundation


Track 2: Financial Services s

Case Study: Scotiabank

Mortgage liquidation Model Building and ApplicationThe purpose of development of a mortgage liquidation model is to enable Group Treasury and Asset liability Management to reduce cash flow uncertainty and improve budgeting and hedge effectiveness. A multinomial logistic regression model was built to predict two mortgage events: full payment and early renewal.


Intellig nt Enterpr ses

don’t merely c mpete,

they outc mpete


The model was vetted by validation team, and applied to cash flow analysis and gap reporting.

Speakers: Jane Zhong, Senior Manager of Predictive Analytics, Scotiabank

Wenlei Shi, Data Mining Analyst, Scotiabank

11:40am-12:00pm • Room: Salon 5 & 6

Track 1: Survey Analysis l

Case Study: Cox Communications

using Analytics to Guide the Creation of Creative for Segment-Targeted CampaignsThis session extends a relatively new area of analytics - the use of predictive techniques to generate success-elevating insights into consumer decision psychology. We’ll begin by reviewing the qualitative technique of laddering interviews and its resulting maps of consumer thought

that have been a proven source of marketing strategy and creative guidance. Its problem has been that it is too expensive to do enough research to fully understand the nuanced motivational differences between segments. We’ll continue by showing how specialized survey data can be analyzed in a way that can extend laddering insights down to the segment level.

Speaker: Bob Wood, Director – Analytics Product Team, Merkle Inc.

11:40am-12:00pm • Room: Golden Gate A

Track 2: uplift Modeling s

Case Study: Intuit

uplift Modeling - Direct Marketing Case StudiesSeveral million customers use Quicken and Quick Books. Understanding the effectiveness of marketing campaigns is essential to Intuit for customer retention. In this case


! !!

Inkiru!Data-driven companies are growing out of their diagnostic analysis and visualization phase and advancing into a real-time predictive analytics phase. The Inkiru Predictive Intelligence™ Platform accelerates this evolution by hosting real-time predictive models, guiding business decisions by generating scores and recommendations that enhance business performance. Inkiru Differentiators Only Inkiru is able to enhance customer activation and targeting, optimize campaigns, minimize fraud and reduce risk by:

• Utilizing real-time predictive analytics within the live transaction path. • Blending linkage and time series information from Inkiru’s Predictive Graph with customer,

transactional, and external data. • Providing a holistic view of each customer and their relationship with other customers and products

on your site. • Providing a real-time decision engine with dashboards and monitoring • Enabling an analytics sandbox for experimentation prior to deploying the models in production • Continually refreshing models and databases to stay current with relevant business fluctuations.

Inkiru’s platform supports models created in SAS, R, and other environments; and it minimizes engineering integration time, ensuring rapid deployment and management of models. Delivered as a secure hosted solution, the Inkiru Predictive Intelligence™ Platform minimizes the significant investment of building and maintaining an in-house infrastructure, ensuring that businesses of all sizes can quickly leverage the power of real-time predictive analytics for customer interactions. !


study, we describe how we implemented uplift models to discover incremental impact attributable solely to the campaigns. The key takeaways from the presentation are:

l How we mine customer data to derive predictors of response

l The discussion of differences in traditional response models and uplift modeling

l To demonstrate effectiveness of uplift modeling in retaining customers

A white paper on this topic is available online at:

www.predictiveanalyticsworld.com/signup-uplift-whitepaper.php

Speakers: Madhu Iyer, Marketing Statistician, Intuit, Inc.

Inna Shapotina, Senior Data Analyst, Intuit, Inc.

12:05-12:25pm • Room: Salon 5 & 6

Track 1: Spam Detection l

Case Study: MailChimp.com

Monkeys & Math: how MailChimp Catches Bad GuysHear from MailChimp’s Chief Scientist John Foreman as he dishes on dirty data and demonstrates the latest in MailChimp’s anti-abuse artificial intelligence. MailChimp sends 3 billion emails a month for their millions of users, and they can’t afford to let a drop of spam go out. learn how the company is using cutting edge noSQl solutions and predictive models to leave the bad guys out in the cold.

Speaker: John Foreman, Chief Scientist, MailChimp.com

12:05-12:25pm • Room: Golden Gate A

Track 2: uplift Modeling s

Case Study: Hewlett-Packard

A Generic uplift Modeling Framework to Calculate ROI - Application in Promotion Effectivenessvarious retail chains in consumer electronics run different discount promotions on HP products round the year where the promotion spends are shared between these chains and HP. In this context, business wanted to know the extent of usefulness of these promotions through a data-driven approach, which can be leveraged in planning, executing and optimizing these spend dollars. As an essential part of the objective, a generic uplift modeling framework was built to calculate ROI for different discount promotions using the statistical technique called AnCOvA in an unconventional way. The successful implementation of this solution led to a huge dollar impact.

A white paper on this topic is available online at:

www.predictiveanalyticsworld.com/signup-uplift-whitepaper.php

Speaker: Jyotirmay nag, Analytics Consultant of RnD Analytics, Hewlett-Packard



12:25-1:30pm • Room: Exhibit Hall

lunch


lunch & learn

Industrialization of Analytics – Enjoy the JourneyThe explosion of Big Data with exponential growth in volume and variety of data has helped and complicated the process of generating insights for business. Through an exchange of ideas, we will discuss an Inside: Outside perspective on industrializing the process to convert data into insights, insights into smart business decisions and action. We will take you through this journey through a series of anecdotes and case studies from two different perspectives. David Kreutter, vP Global Business Analytics and Insights at Pfizer will present expert view on his journey and how you can take your organization

through it successfully. Pankaj Kulshreshtha, Business leader, Analytics and Research at Genpact will bring in his experiences of analytics evolution journeys from partnering with clients across industries.

Speakers:

Pankaj Kulshreshtha, Business leader, Analytics & Research, Genpact

David Kreutter, vP Business Analytics and Insights, Pfizer


keynote

Analytics and the Presidential ElectionsThis talk will describe how the Obama Campaign used analytics to improve decision making in virtually every function within the organization. We’ll talk about how data from a variety of sources was used to improve fundraising, volunteer recruiting and mobilization, media



targeting, and optimize voter contacts. We will cover what kind of data was available to the campaign, what technologies were developed and/or used, and how the resulting products were adopted by the campaign in order to help win the presidential elections. Although the focus will be on the elections and politics, we’ll also talk about lessons learned during the campaign and how some of the same techniques can be applied to other industries and organizations.

Speaker: Rayid Ghani, Chief Data Scientist, Obama for America


Vendor Elevator Pitches

2:35-2:55pm • Room: Salon 5 & 6

Track 1: eCommerce Analytics l

Case Study: Minted.com

Mining Customer Behavior for Targeted MarketingModern marketing tools enable very targeted messaging and offers. The challenge is to understand our customer and prospects well enough to come up with the offer and surrounding message that will resonate in a timely way with each individual. There are two steps in meeting the challenge. First, we need to pick strategies that are practical and have real economic benefits. next, invent the tactics which enable these strategies.

In this case study, you will learn how Minted mines our customer initiated actions from logs of interactions with our site, responses to our email and print campaigns, and other customer touch points to target customers with optimal offers and engaging messages.

Speakers:

Jim Porzak, Senior Director, Business Intelligence, Minted

Anne-Elise lansdown, Marketing Manager, Minted

3:00-3:20pm • Room: Salon 5 & 6

Track 1: Analytics Team Building & Management l

Case Study: Netflix

Building a Data Science Team from ScratchIn this session, netflix analytical leader Chris Pouliot shares his experience building a large team of data scientists at netflix. He formed a central, horizontal team for the company, which spans across all business verticals. Chris shares many interesting insights and stories, covering pitfalls and successes experienced as he built the team, as well as the great successes and positive impact at netflix achieved.

Speaker: Chris Pouliot, Director, Algorithms & Analytics, netflix


Track 2: Advanced Methods s

Case Study: Qualcomm

M.A.R.S. - an underused Modeling MethodThe flexibility and power of using the Multivariate Adaptive Regression Splines (M.A.R.S.) approach to predict the demand of a product or the find optimal performance characteristics of a semiconductor chip will be discussed. Real world examples will be given demonstrating the capture of trends, such as, weekly, daily, hourly, and holiday effects in a statistical model. The ease of using both numeric and text data will be illustrated. The approach will compared to other approaches such as ARIMA time series, neural networks and multivariate regression.

Speaker: Maria lupetini, Engineering Advanced Analytics and Asset Management, Qualcomm Technologies Inc.


Exhibits & Afternoon Break



3:50-4:10pm • Room: Salon 5 & 6

Track 1: Search Engine Marketing l

Case Study: Kelley Blue Book

Driving Search Engine Marketing with Deep AnalyticsThis session provides a deep dive into a case study about Search Engine Marketing (SEM) profit maximization and techniques used to identify when is the best time to stop spending on cost-per-click advertising. We will share a simple user-friendly model, in addition to discussing the need for a more robust approach, to identify diminishing returns in SEM spend, while addressing core challenges of both approaches. This session will provide analysts and analytics leadership with an effective framework to improve SEM spend efficiency, accuracy and applicability to meet business objectives.

Speaker: Shawn Hushman, vice President of Advanced Analytics, Kelley Blue Book

3:50– 4:35pm • Room: Golden Gate A

Track 2: Insurance/Fraud Detection s

Case Study: Selective Insurance Group

Strategies and Considerations for Fraud Detection in Insurance ClaimsBy embedding analytics into its’ claim handling Selective Insurance Group, Inc. (SIGI nASE), a top 40 P+C insurance carrier, has significantly increased its SIU activities as measured by the number and proportion of claims it classifies as fraudulent. In general, insurance fraud can be very difficult to detect. Common challenges include text mining, unstructured data, censored data, small and biased samples, measuring success, etc. This presentation will focus on some of the lessons-learned in the identification of insurance fraud and the challenges of deploying automated analytic tools in insurance claims handling.

Speaker: Bob Biermann, Senior Econometrician, Selective Insurance Group



4:15-4:35pm • Room: Salon 5 & 6

Track 1: Budgeting & Macroeconomics l

Case Study: Hewlett-Packard

An Innovative Approach to hedge Against Macroeconomic uncertainties Affecting BusinessesBusinesses are continuously faced with margin pressures due to the impact of macroeconomic headwinds caused by inflation, exchange rate, interest rate and GDP. A 2-step innovative prediction framework is developed to hedge against these externalities. At the first step, income statement variables, i.e. revenue, COGS, SG&A are forecast factoring in the impact macroeconomic indicators. If there is a gap in the budgeted and forecast numbers, the second step establishes the relationship between cost drivers and income statement variables through multiple simulations. This enables the leadership conduct scenarios to achieve more realistic forecasts based on prevalent and forecast macroeconomic uncertainties.

Speakers:

Srinidhi Srinivasan, Analytics Consultant, Hewlett-Packard

Keshav loomba, Manager - Global Analytics Finance, Hewlett-Packard

Ashish Kumar Singh, Global Analytics, Strategic Consulting and Business Planning, Hewlett-Packard

4:40pm–5:25pm • Room: Salon 5 & 6

Track 1: Industry Skills l

Case Study: Orbitz

Delivering on Expectations: Core Competencies for Data ScientistsThe McKinsey Institute predicts a need for 1.5 million additional mangers and analysts in the United States who can ask the right questions and consume the results of the analysis of big data effectively. This session is geared for statistical modelers and advanced analytics professionals. You will learn about the changing landscape and the skill sets required for data miners in the new era of Big Data.

While statistical modeling is not going away, analytics groups are advised to leverage machine-learning approaches as well.

While traditional statistical modeling software packages are not going away, analytics groups need to actively embrace new skill-sets in emerging software such as open-source tools (e.g., R, MongoDB) and Big Data tools (e.g: Hadoop).

Speakers: Sameer Chopra, vice President of Advanced Analytics, Orbitz Worldwide

Wenqing lu, Director, Statistical Modeling and Analytics, Orbitz Worldwide

4:40–5:25pm • Room: Golden Gate A

Track 2: Insurance s

Case Study: Broadspire

To Sue or Not to Sue: Predicting litigation Risklitigation is a major cost factor in handling casualty claims. Follow the development and testing of a double barreled litigation prediction application for our claims system and our parallel e-Triage system, which provides a richer data environment for certain types of insurance claims. This is a major enhancement of a robust predictive system now in use for over six years and an expansion of predictive know-how to control claim costs. See how we apply our continuous improvement philosophy to making predictive analytics a core competency inside an industry leading claims service.

Speakers:

Gary Anderberg, Practice leader, Analytics and Outcomes, Broadspire

Bangalore Gunashakar, Senior Technical Consultant, Broadspire

Sergo Grigalashvili, vP Architecture, Analytics, GSR, Crawford & Company


Networking Reception




Bay Area SAS users Group Meeting

lOCF Programming in Clinical Trial AnalysisSpeaker: Albert Mo

Pharmaceutical and biotech companies often conduct longitudinal studies on human subject that spend several visits (weeks or months.) There are many situations where subjects do not following instructions, skip scheduled visits, or drop out of the study all together. These result in missing data in the datasets.

lOCF is a method used to deal with these missing data in Clinical Trial Analysis. It stands for “last Observation Carried Forward.” And it is a common imputation method used to impute missing values and missing visits.

This paper will explain the lOCF concept, demonstrate the programming framework, and introduce sample SAS code to accomplish lOCF

SAS – Integrated Object ModelSpeaker: Kenneth M. lin

• Fun with SAS Integrated Object Model (IOM)

• Creating Interactive SAS Driven Report Infrastructure using MS Excel and vBA

For more information on the event please go to: www.basas.com/

7:00-10:00pm • Room: Golden Gate B

Bay Area useR Group Meeting



Conference Day 2Tuesday, April 16, 2013

8:00-9:00am • Room: Foyer

Registration & Networking Breakfast


Conference Chair Welcome Remarks Speaker:

Eric Siegel, Ph.D., Conference Chair, Predictive Analytics World


Diamond Sponsor Presentation

Transform your Future with Predictive AnalyticsThe measure of intelligence is the ability to change.” – Albert Einstein. never has this statement been truer than in today’s world of real-time data…. where an organization or an individual can either prosper or perish by the quality of a decision. The data has always been out there. Finally, now we possess the technology to truly harness it. Imagine what might happen if you could run “what-if” scenarios at lightning speed. Or empower everyone in your organization to visualize the possibilities. now is the time, and you are the person to decide to seize

that opportunity. What would you do tomorrow if there were no limitations? Join John MacGregor, vP and Head of the Centre of Predictive Analytics at SAP, to discover how new technologies can help you transform your future.

Speaker: John MacGregor, vP and Head of the Centre of Predictive Analytics, SAP


keynote

Putting IBM Watson to WorkIBM’s Watson captured the imagination of millions when it beat the all time champions of the US game show, Jeopardy!. To do so, it overcame traditional limitations of computers by communicating in natural human language, churning through 200 million pages of unstructured data to find answers in three seconds, and learning from each experience to improve performance over time. But as impressive as this accomplishment was, it was only the beginning. IBM is working closely with leading organizations in a variety of industries to put Watson to work. The possibilities are endless! Join Edward nazarko, a leading IBM Architect, in an engaging discussion of ways that Watson is using predictive models to revolutionize expectations of how computers can help organizations in all industries live and work better.

Speaker: Edward nazarko, Client Technical Advisor, IBM

Session DescriptionsTuesday, April 16, 2013



10:10-10:40am • Room: Exhibit Hall

Exhibits & Morning Coffee Break



Applying Predictive Analytics in Real-TimeProduct demonstration to illustrate how events are processed through customized models hosted on the Inkiru Predictive intelligence™ Platform. Every time an event occurs on a merchant’s website it gets logged in our graphing and metric database. Attendees will learn how we traverse our graph, map it to corresponding metrics, run data through the customized models, and return a highly accurate score in less than 500 milliseconds. Once the merchant is provided with the score, they can personalize their interaction for each customer.

Speaker: Jaya Kolhatkar, CAO, Inkiru, Inc

10:50-11:10am • Room: Salon 5 & 6

Track 1: Industry News l

using Analytics to Build your Analytics Bench: Announcing 2012 Analytics Professionals Study ResultsMany innovative businesses and IT organizations appreciate the competitive advantage analytics capabilities can provide and have ambitions to reach increasing levels of analytics maturity. However, the well-documented shortage of analytic talent leaves many firms without a strong analytic talent bench and little knowledge about how and where to find analytics professionals needed to get there. In this presentation, Greta Roberts will discuss results from a major 2012 Study of Analytics Professionals that crosses industries, experience and skills. Practical insights shared include key best practices, trends and correlations that lend unexpected insight into building a strong and scalable analytic talent bench.

Speaker: Greta Roberts, Faculty Member, International Institute for Analytics


Track 2: Thought leadership s

My Five Predictive Analytics Pet PeevesPredictive Analytics (PA) has become increasingly mature as a technical discipline over the past decade in part because it stands on the shoulders of the related disciplines of data mining and machine learning. However, there are recurring themes that permeate discussion boards and conferences that have become my personal pet peeves. This talk examines five of them and why they matter to practitioners, including why we must have humility in how far data science and algorithms can take us, and the value of business objectives, measuring success, and measuring significance.

Speaker: Dean Abbott, President, Abbott Analytics, Inc.

11:15–11:35am • Room: Salon 5 & 6

Track 1: Cross-Enterprise Analytics l

Case Study: Monster Worldwide

Win With Advanced AnalyticsMonster was the pioneer in the online recruitment industry. To maintain its competitive advantage, it has taken the data-driven road using research, business intelligence and predictive analytics and text analytics. Join this session to hear how Monster went from good to great using business analytics to support its overall decision-making process across all regions. Jean-Paul Isson will provide highlights from his new book, Major Steps to Win with Analytics with the Big Data. He will also discuss Monster’s success with increasing customer retention, market share and customer profitability, while managing competition from paid sites, free sites and social networks.

Speaker: Jean-Paul Isson, Global vP Predictive Analytics & BI, Monster Worldwide



11:15–11:35am • Room: Golden Gate A

Track 2: Next Best Offer s

Case Study: Hewlett-Packard and WB Mason

Predicting Next Most likely Supplies Purchase using Multinomial logitCustomer loyalty continues to be a challenge to any marketer and more so in the retail trading business. WB Mason, office supplies providers, realized the same trying to identify the stickiness of their loyal SMB customer base. A 20% loss in each successive cycle of purchase necessitated thinking through a model that can not only capture when these customers are likely to come back for repurchase but also the offer that WB Mason should be making at that point. We use a Repeat purchase model and eventually a Multinomial logit model to understand customer purchase behavior.

Speakers: Avinash Parthasarathy, Analytics Consultant in Global Analytics, Hewlett-Packard

Arpit Jain, Analytics Professional, Global Analytics, Hewlett-Packard

Pallavi Gupta Bhowmick, Analytics Delivery lead, Global Analytics, Hewlett-Packard

11:40–12:00pm • Room: Salon 5 & 6

Track 1: lead Management l

Case Study: Citrix

how Predictive Analytics Changes the Game by Front-Ending the FunnelIn owning the front end of the revenue funnel, marketing has a unique vantage point. In this session, learn how Citrix leveraged the data and insights acquired to build a finely tuned marketing and lead management strategy for their market-leading cloud, collaboration, networking and virtualization technologies. By applying predictive analytics to their model, Citrix was able to increase the campaign effectiveness and lead to opportunity conversion rate. Get guidance from Citrix on how you can apply these methods to increase marketing contribution to the pipeline.

Speaker: Eva Tsai, Senior Director, Marketing Operations, Citrix

12:05–12:25pm • Room: Salon 5 & 6

Track 1: Churn Modeling l

Case Study: Paychex

Customer Retention: Pulling the Needle from the haystackIn these economic times, it is critical for businesses to have a stronghold on client retention, with businesses excelling in this arena better positioned for long-term success. To optimize the value of retention efforts, it’s essential to understand which clients are the best fit for retention campaigns. In this session, we will review how Paychex leveraged two existing models, Paychex Attrition Model and a custom-built lifetime value Model, to create a Retention Tracking System (RTS). Since being deployed across the entire branch network, the RTS has become an invaluable resource as offices nation-wide strive to meet, and exceed, retention goals.

Speaker: Frank Fiorille, Sr. Director of Risk Management, Paychex, Inc.


Track 2: Brand Analytics s

Case Study: Dell

The Illusive Brand: how to Measure Brand and the Communications Focused On ItMeasuring a brand health is very difficult and can be convoluted. Often, if you have multiple metrics such as nPS or survey results, they will not align on how your brand health is changing. Helping business leaders understand how they can impact brand health is even more difficult. natalie will present ideas on how to model out marketing’s impacts on the brand, measuring the long-term impacts of an overriding campaign, and how to handle differing trends from various brand health metrics. In addition, we will discuss how to explain these models and their errors to decision makers.

Speaker: natalie Kortum, Marketing Decision Scientist, Dell



12:25–1:30pm • Room: Exhibit Hall

lunch


Platinum Sponsor Presentation

Predicting a Fraudulent Payment – Is it possible?Investigating disbursement fraud typically happens ex post facto. The deed is done; the money has left the account. In the notion that prevention is better than detection, there is a need to find ways in which organizations can better protect the leakage of their funds before it is too late. The challenge in prevention of this nature is determining what disbursement may be fraudulent or inappropriate, in real-

time, without throttling business operational effectiveness, and impacting the overall bottom-line.

Given the observations around the rapid evolution of predictive analytic capabilities, perhaps an innovative way forward would be to consider an in-line predictive risk-driven continuous monitoring mechanism, which filters those pending disbursements based on fluxing risk indications of events preceding the actual payment.

This presentation walks through an innovative approach and architecture, as to how this might be practically achieved with today’s techniques and approaches, in a corporate setting.

Speaker:

Josh Ellis, Director, Data Analytics, Deloitte Financial Advisory Services llP


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Predictive Analytics World



Special Plenary Session

General lessons We Can learn from Blackbox TradingBeating the market with skill, rather than luck, is so hard that it’s arguably impossible. A strong working approximation is that markets are efficient - that prices reflect available information almost instantaneously. Accordingly, we have failed often. But our success building quantitative investment systems has been great - most notably with a hedge fund that beat the S&P-500 every year for a decade, with only 2/3rds the risk (volatility). This talk will highlight key lessons learned from the long battle, and how those insights have helped solve many other predictive analytics challenges.

Speaker: Dr. John Elder, CEO and Founder, Elder Research, Inc.


Expert Panel

Big Data for Predictive AnalyticsIf Big Data begs the question, “What to do with all this data?” predictive analytics answers, “learn from it to predict behavior.” But just how much predictive payoff comes with going so big? This expert panel will address the new demands on predictive analytics solutions and best practices as data grows to enormity, and will recommend tactics to fully leverage data’s growing magnitude to improve the business performance of predictive analytics initiatives.

Moderator: Eric Siegel, Ph.D., Predictive Analytics World

Panelists: Satish lalchand, Director, Deloitte Financial Advisory Services llP

Anil Kaul, CEO and Co-Founder, AbsolutData

3:25–3:50pm • Room: Exhibit Hall

Exhibits & Afternoon Break


Track 1: Data Visualization l

Case Study: Wells Fargo

Data Visualization Design using Shneiderman’s Mantra: Overview First, Zoom and Filter, Then Details-On-DemandThis session explores applications of Shneiderman’s mantra for visual data analysis (overview first, zoom and filter, then details-on-demand) as a framework in the context of three complex analytical applications at Wells Fargo:

1 - Analytics Process

2 - Interactive Meeting Facilitation

3 - Dashboard Design

Speakers:

Eric legrand, Marketing Database Consultant, Wells Fargo

Dana Zuber, Strategy and Analytics Executive, Wells Fargo


Track 2: likelihood-to-Recommend s

Case Study: AAA

Multicollinearity and Sparse Data in key Driver Analysis: Challenges and SolutionsAAA-nCnU is a membership organization with multiple products ERS, insurance, travel, and car care. Determining key drivers of likelihood-to-Recommend is complicated by the multicollinearity among some attributes and by other attributes, filtered based on experience. The first challenge was addressed through Shapley Regression, while the second was handled through bivariate linear regressions adjusted for incidence. With these two methods, we were able to estimate the relative impact of the drivers expressed in percentages. The company used the results for prioritizing decisions and allocating resources.

Speakers: noe Tuason, Experience Insights & Analytics Manager, AAA-nCnU

Raymond Reno, Senior vice President, Market Strategies International




Track 2: Insurance & hR Analytics s

Case Study: Crawford Global Technical Services

using Predictive Analytics for Strategic Planning at Crawford GTSWhen the nature of business heavily depends on natural events, market condition, and individual professional relations, how does Crawford & Company manage the global work force of +500 executive general adjusters optimally? We mine proprietary data for the most complex insurance claims to forecast demand by geography, industry, insurer, and peril. We also analyze work force profile and combine the forecasted demand with supply for strategic planning for each region and industry. This presentation covers the approach we use to manage hundreds of models cost effectively for three objectives:

1 - Managing Global Work Force

2 - Optimizing Business Operations

3 - Improving Client Relations

Speakers: Sergo Grigalashvili, vP Architecture, Analytics, GSR, Crawford & Company

Dr. Andries Willemse, SvP, Crawford Global Technical Services, Crawford & Company

4:40-5:30pm • Room: Salon 5 & 6

Track 1: Data Visualization l

Case Study: Blue Shield of California

No Country for Fat Men - Investigating Obesity with Visual Analyticsvisual analytics is gaining importance due to the explosion of data availability and processing capabilities. In this example, we demonstrated the power of visual analytics

to investigate various aspect of obesity using a readily available commercial product called Tableau on the CHIS (California Health Interview Survey). A recent JAMA article claimed that there was no time to waste in doing obesity research and a broad-based effort was needed. Since CHIS tracked responses to hundreds of questions, our demonstration provided an excellent example of how visual analytic tools could empower end-users to find interesting relationships within a morass of data.

Speaker: Aaron lai, Senior Manager, Marketing Analytics, Blue Shield of California


Track 2: hR Analytics s

Case Study: ConAgra Foods

Aging of the Baby Boomer Generation and the upcoming Talent TsunamiOver the next 10 years, approximately 40% of ConAgra Foods’ workforce will become retirement eligible. With 25,000 employees across seven business units and almost 90 locations, the task of understanding, analyzing and solving for the demand was monumental. As a $14 billion consumer packaged goods company, ConAgra Foods’ strategy or Recipe for Growth would be fueled by transforming the organization’s culture, winning in talent acquisition, and accelerating development of existing employees. During this session, we will discuss how to leverage existing data and predictive analytics to transform the organization’s approach to talent.

Speakers: KC Bradley, Manager, Integrated Talent Management, ConAgra Foods, Inc.

Sara Roberts, leader, Advanced Analytics, ConAgra Foods, Inc.



Conference Workshops

Sunday, April 14, 2013Full-Day: 9:00am - 4:30pm • Room: Salon 5 & 6

R for Predictive Modeling:A hands-On Introduction

Intended Audience: Practitioners who wish to learn how to execute on predictive analytics by way of the R lan-guage; anyone who wants “to turn ideas into software, quickly and faithfully.”

knowledge level

Either hands-on experience with predictive modeling (without R) or hands-on familiarity with any programming language (other than R) is sufficient background and preparation to participate in this workshop.

Workshop Description

This one-day session provides a hands-on introduction to R, the well-known open-source platform for data analysis. Real examples are employed in order to methodically expose attendees to best practices driving R and its rich set of predictive modeling packages, providing hands-on experience and know-how. R is compared to other data analysis platforms, and common pitfalls in using R are addressed.

The instructor, a leading R developer and the creator of CARET, a core R package that streamlines the process for creating predictive models, will guide attendees on hands-on execution with R, covering:

• A working knowledge of the R system

• The strengths and limitations of the R language

• Preparing data with R, including splitting, resampling and variable creation

• Developing predictive models with R, including decision trees, support vector machines and ensemble methods

• visualization: Exploratory Data Analysis (EDA), and tools that persuade

• Evaluating predictive models, including viewing lift curves, variable importance and avoiding overfitting

hardware: Bring your Own laptop

Each workshop participant is required to bring their own laptop running Windows or OS x. The software used during this training program, R, is free and readily available for download.

Attendees receive an electronic copy of the course materials and related R code at the conclusion of the workshop.

Schedule• Workshop starts at 9:00am

• Morning Coffee Break at 10:30am - 11:00am

• lunch provided at 12:30 - 1:15pm

• Afternoon Coffee Break at 2:30pm - 3:00pm

• End of the Workshop: 4:30pm

Instructor: Max kuhn, Director, Nonclinical Statistics, Pfizer



Tuesday, April 16, 2013Full-day: 9:00am - 4:30pm • Room: Foothill E

Making Text Mining Work: Practical Methods and SolutionsA free copy of Dr. Fast’s book on Practical Text Mining is

included.

Intended Audience

Practitioners seeking tools to analyze unstructured text data.

knowledge level

no previous experience required though some technical background in statistics or predictive analytics will be useful.

Attendees will receive an electronic copy of the course notes via USB drive.


In their 2011 Hype Cycle report, Gartner has Text Analytics sliding into the “Trough of Disillusionment”, highlighting the difficulty of achieving its great promise. Despite this verdict, text mining and text analytics can be valuable tools, if you know where to look for the solution. This workshop will address:

• The text mining solutions available now and the problems for which they are best suited

• Best practices in the key text mining areas

• How to set positive but realizable expectations for the return on investment of a text mining project

This one-day session surveys standard and advanced methods for text mining. Dr. Fast will describe the key inner workings of leading algorithms, demonstrate their performance with business case studies, compare their merits, and show how to pick the approach best suited for your project. Methods covered include search indexes, text classification, information extraction, document similarity and more.

The key to successfully leveraging these methods is to find the right “hammer” for your text “nails” and understand the limits of those techniques.

Dr. Fast will share his experience mining text on real-world applications in several fields, highlighting the range of available solutions and how to combine technologies to maximize the value of the vast store of (untapped) unstructured data.

If you’d like to become a text mining practitioner – or if you already are, and would like to hone your knowledge across methods and best practices, this workshop is for you!

What you will learn• The tremendous value of learning from unstructured

textual data

• How to choose the proper text mining solution

• Text mining best practices

Schedule

• Workshop starts at 9:00am

• First AM Break from 10:00am - 10:15am

• Second AM Break from 11:15am - 11:30am

• lunch from 12:30pm - 1:15pm

• First PM Break: 2:00pm - 2:15pm

• Second PM Break: 3:15pm - 3:30pm

• Workshop ends at 4:30pm

Attendees receive a free copy of Andrew Fast’s book on Practical Text Mining, an electronic copy of the course notes via USB drive, and an official certificate of completion at the conclusion of the workshop.

Instructor: Dr. Andrew Fast, Director of Research, Elder Research Inc.



Tuesday, April 16, 2013Three Hours: 6:30pm - 9:30pm • Room: Foothill E

Mapping Groups of People and What They are Talking About in Social Media

Intended Audience

Social media managers and analysts, marketers, collaboration and enterprise IT, advertisers, event planners, journalists,

knowledge level All skill levels, beginners particularly welcome. Should have an interest in social media. Any experience with a spread-sheet is a plus!


Social media conversations are clumpy. People tend to follow and reply to people who share their views so distinct clusters emerge in many social media discussions. Often these sub-groups have distinct ways of using language, point to different URls, and mention different hashtags, even when talking about the same topic. Simple, free and open tools can now collect and analyze these clusters of discussion, highlighting the contrasting themes in the conversation. learn how to perform key tasks like:

• Collect social media data from Twitter, Facebook, YouTube, email, flickr, WWW, message boards and other data sources

• Analyze social media network data using clustering, network metrics, and visualization

• Generate summaries of text, word usage, URls, hahstags, and usernames

• leverage network insights to improve engagement in conversations

This evening session provides a quick end-to-end guide to creating a social media network map with content analysis using free and open tools. Dr. Smith will demonstrate how text from social media can be clustered by applying social network techniques. An entertaining review of social science concepts and tools will provide the context for understanding social media in terms of networks.

If you can make a pie chart, new tools like the free and open nodexl (http://nodexl.codeplex.com) make it almost as easy to make a network chart.

If you would like deeper understanding of the social media landscape around your business and brands, this workshop is for you.

What you will learn:

• Basic concepts of network analysis

• How to apply network analysis to social media

• How to summarize the discussion of multiple groups in social media

• How to identify key influential people and leading sub-groups

Example social analysis, applied to the PAW conference itself:

Schedule• Workshop starts at 6:30pm

• 6:30 Mapping PAWCOn: a guide to network mapping of social media topics

• 7:30 network concepts: key ideas for understanding collections of connections

• 8:30 Social Media networks: data collection, automated analysis, summarizing text

• Workshops ends at 9:30pm

Instructor: Marc A. Smith, Chief Social Scientist, Connected Action Consulting Group


Wednesday, April 17, 2013 Full-Day: 9:00am - 4:30pm • Room: Pacific J

Supercharging Prediction: hands-On with Ensemble Models

Sponsored By:

Intended Audience:

Practitioners: Analysts who would like to learn how to build and gain insight from model ensembles using a state-of-the-art data mining software tool.

Technical Managers: Project leaders and managers who are responsible for developing predictive analytics solu-tions and want to understand the potential value and limitations of model ensembles.

knowledge level

Basic understanding of statistical methods or predictive modeling algorithms


Once you know the basics of predictive analytics including data exploration, data preparation, modeling building, and model evaluation, what can be done to improve model accuracy? One key technique is the use of model ensembles, which “groups” or “rolls up” models into a single, usually-better model.

Are model ensembles an algorithm or an approach? How can one understand the influence of key variables in the ensembles? Which options affect the ensembles most? This workshop dives into the key ensemble approaches including Bagging, Random Forests, and Stochastic Gradient Boosting. Attendees will learn “best practices” and attention will be paid to learning and experiencing the influence various options have on ensemble models so that attendees will gain a deeper understanding of how the algorithms work qualitatively and how one can interpret resulting models. Attendees will also learn how to automate the building of ensembles by changing key parameters.

Participant Background

Participants are expected to know the principles of predictive analytics. This hands-on workshop requires all participants to be involved actively in the model building process, and therefore must be prepared to work independently or in a small team throughout the day. The instructor will help participants understand the application of predictive analytics principles and will help participants overcome software issues throughout the day.

Software

The key concepts covered during this workshop can be applied to many predictive analytics projects regardless of the software employed. However, for this workshop’s hands-on experience, Salford System’s SPM suite will be used. SPM is a state-of-the art software package known for its capabilities in building model ensembles. A license will be made available to participants for use on that day (included with workshop registration).


Each workshop participant is required to bring their own laptop running Windows; both PCs and Macintoshes running Windows (through Parallels Desktop or Fusion are acceptable). It is strongly recommended that the software be installed prior to the workshop by visiting the Salford Systems booth in the Predictive Analytics World exposition hall and installing the software from CD or USB.

Attendees receive a course materials book and an official certificate of completion at the conclusion of the workshop.

Schedule• Software installation (if not already installed): 8:30am

• Workshop program starts at 9:00am

• Morning Coffee Break at 10:30 - 11:00am


• Afternoon Coffee Break at 2:30 - 3:00pm


Instructor: Dean Abbott, President, Abbott Analytics



Wednesday, April 17, 2013Full-Day: 9:00am - 4:30pm • Room: Pacific H

The Best and the Worst of Predictive Analytics: Predictive Modeling Methods and Common Data Mining Mistakes

Intended Audience: Interested in the nuts and bolts

Knowledge level: Familiar with the basics of predictive modeling.

Statements of testimony:

“You don’t know what you don’t know ... after this course, I now know what I don’t know and what I should develop greater understanding in for both myself, my company and our clients”

Sean Liddle, Deloitte

“Some very complex topics were explained very comprehensively and clearly, and put into a wider context of how to use these in real-life situations.”

Colin Styles, Information Architect, Sussex Health Informatics Service


Predictive analytics has proven capable of enormous returns across industries – but, with so many core methods for predictive modeling, there are some tough questions that need answering:

• How do you pick the right one to deliver the greatest impact for your business, as applied over your data?

• What are the best practices along the way?

• And how do you avoid the most treacherous pitfalls?

This one-day session surveys standard and advanced methods for predictive modeling.

Dr. Elder will describe the key inner workings of leading algorithms, demonstrate their performance with business case studies, compare their merits, and show you how to pick the method and tool best suited to each predictive analytics project. Methods covered include classical

regression, decision trees, neural networks, ensemble methods, uplift modeling and more.

The key to successfully leveraging these methods is to avoid “worst practices”. It’s all too easy to go too far in one’s analysis and “torture the data until it confesses” or otherwise doom predictive models to fail where they really matter: on new situations.

Dr. Elder will share his (often humorous) stories from real-world applications, highlighting the Top 10 common, but deadly, mistakes. Come learn how to avoid these pitfalls by laughing (or gasping) at stories of barely averted disaster.

If you’d like to become a practitioner of predictive analytics – or if you already are, and would like to hone your knowledge across methods and best practices, this workshop is for you!

What you will learn:

• The tremendous value of learning from data

• How to create valuable predictive models for your business

• Best Practices by seeing their flip side: Worst Practices

Schedule• Workshop starts at 9:00am

• First AM Break from 10:00 - 10:15am

• Second AM Break from 11:15 - 11:30am

• lunch from 12:30 - 1:15pm

• First PM Break: 2:00 - 2:15pm

• Second PM Break: 3:15 - 3:30pm

• Workshops ends at 4:30pm

Attendees receive a free copy of John Elder’s book Statistical Analysis and Data Mining Applications, an electronic copy of the course notes via USB drive, and an official certificate of completion at the conclusion of the workshop.

Instructor: Dr. John Elder, CEO & Founder, Elder Research, Inc.



Thursday, April 18, 2013

Full-Day: 8:45am - 4:30pm • Room: Pacific B

Advanced Methods hands-On:Predictive Modeling Techniques

Sponsored By:

Intended Audience Practitioners: Analysts who would like a tangible introduc-tion to predictive analytics or who would like to experience analytics using a state-of-the-art data mining software tool.

Technical Managers: Project leaders, and managers who are responsible for developing predictive analytics solu-tions, who want to understand the process.

knowledge level

Familiar with the basics of predictive modeling.


Once you know the basics of predictive analytics and have prepared data for modeling, which algorithms should you use? What are the similarities and differences? Which options affect the models most? This workshop dives into the key predictive analytics algorithms for supervised learning,including decision trees, linear and logistic regression, neural networks, k-nearest neighbor, support vector machines, and model ensembles. Attendees will learn “best practices” and attention will be paid to learning and experiencing the influence various options have on predictive models so that attendees will gain a deeper understanding of how the algorithms work qualitatively.

Participant background

Participants are expected to know the principles of predictive analytics. This hands-on workshop requires all participants to be involved actively in the model building process, and therefore must be prepared to work independently or in a small team throughout the day. The instructor will help participants understand the application of predictive analytics principles, and will help participants overcome software issues throughout the day.

Software

While the majority of concepts covered during this workshop apply to all predictive analytics projects - regardless of the particular software employed - this workshop’s hands-on experience is achieved via StatSoft STATISTICA. A license will be made available to participants for use on that day (included with workshop registration).


Each workshop participant is required to bring their own laptop running Windows. Instructions will be provided to install a trial license for the analytics software used during this training program.

Attendees receive a course materials book and an official certificate of completion at the conclusion of the workshop.

Schedule

• Software installation at 8:45am

• Workshop program starts at 9:00am

• Morning Coffee Break at 10:30 - 11:00am


• Afternoon Coffee Break at 2:30 - 3:00pm


Instructor: Dean Abbott, President, Abbott Analytics



Friday, April 19 and Saturday, April 20, 2013Full Day (Friday): 9:00am-4:30pm

Half Day (Saturday): 9:00am-12:00pm

Room: Foothill D

Net lift Models: Optimizing the Impact of your Marketing

Intended Audience: Statisticians, business analysts, and market researchers who build predictive models for mar-keting and retention campaigns.

Response modeling is the wrong modeling! Whatever your response rate, what about those customers who would have purchased anyway without expending the cost of contact? If retention offers targeted by a churn model save some customers, what about the “casualties,” i.e., the customers who respond adversely to this contact but who would have stayed if left alone? net lift modeling, a.k.a. uplift, incremental lift or true lift modeling, addresses these very issues.


The true effectiveness of a marketing campaign isn’t response rate, it is the incremental impact - that is, additional revenue directly attributable to the campaign that would not otherwise have been generated. Yet traditional targeting criteria are often designed to find clients that are interested in the product, but would have bought it anyway, whether or not they received a promotion. In such cases, the incremental impact is insignificant and the marketing dollars could have been spent elsewhere.

net lift Models are designed to maximize incremental impact by targeting the undecided clients that can be motivated by marketing. These “swing customers” are akin to the swing states of a political election; data miners could learn a lot from political campaigns.

Beyond targeted marketing, net lift methodology delivers tremendous performance improvements for deployed churn models - retaining “savables” while avoiding the adverse “reverse” affects retention outreach triggers for some customers - as well as other innovative business applications of this advanced analytical method.

This workshop demonstrates how to build net lift Models that optimize the incremental impact of marketing campaigns, covering the pros and cons of various core analytical approaches.

you Will learn how To

Build net lift models that maximize the difference in response rates between the clients who receive the offer and those that do not (the control group)

• Identify good incremental lift predictive variables

• Build net lift models using a variety of techniques

• Evaluate and deploy net models

Specific Topics Covered Include:

• net lift models versus propensity models

• Example net lift models in action

• Comparison of net lift modeling approaches, including regression- and non-regression-based methods, and the Generalized naive Bayes Classifier

Access to working code and real examples. In order to illustrate net lift modeling in action and provide options for “take-home” usage, the instructor will provide 1) example datasets and 2) examples of code implementing incremental lift modeling methods, including the following SAS macros: InCREMEnTAl, InFORMATIOn, GnBCREG, nWOE (net weight of evidence), and nIv (net information value).

While very advanced attendees may optionally bring their own laptop and software to try out net lift modeling during the workshop, this concentrate topics course does not include enough time for guided hands-on instruction; it is not designed or intended as a “hands-on” training program.

This workshop is offered in cooperation and special arrangement with SAS Institute.

Schedule• Coffee breaks and lunch are included on both days.

Attendees receive a copy of the course materials book at the beginning of the workshop.

Instructor: kim larsen, Vice President of Analytical Insights, Market Share Partners



On-Demand Workshop

Predictive Analytics Applied – An Online IntroductionNew to predictive analytics? Take this online course to ramp up before Predictive Analytics World.

Online 5 ½-hour training program:• On-demand at any time – start now for 3 months of access• Self-paced e-learning – at your convenience• Internationally-friendly – taken from over 16 countries

Instructor: Eric Siegel, Ph.D., Founding Chair, Predictive Analytics World

Intended Audience:• Managers.Projectleaders,directors,CXOs,vicepresidents,investorsanddecisionmakersofanykindinvolvedwithanalytics,

directmarketingoronlinemarketingactivities.

• Marketers.Personnelrunningorsupportingdirectmarketing,responsemodeling,oronlinemarketingwhowishtoimproveresponseratesandincreasecampaignROIforretention,upsellandcross-sell.

• TechnologyExperts.Analysts,BIdirectors,developers,DBAs,datawarehousers,webanalysts,andconsultantswhowishtoex-tendtheirexpertisetopredictiveanalytics.


Businessmetricsdoagreatjobsummarizingthepast.Butifyouwanttopredicthowcustomerswillrespondinthefuture,thereisoneplacetoturn—predictiveanalytics.Bylearningfromyourabundanthistoricaldata,predictiveanalyticsdeliverssomethingbeyondstandardbusinessreportsandsalesforecasts:actionablepredictionsforeachcustomer.Thesepredictionsencompassallchannels,bothonlineandoff,foreseeingwhichcustomerswillbuy,click,respond,convertorcancel.Ifyoupredictit,youownit.

Thecustomerpredictionsgeneratedbypredictiveanalyticsdelivermorerelevantcontenttoeachcustomer,improvingresponserates,clickrates,buyingbehavior,retentionandoverallprofit.Foronlineapplicationssuchase-marketingandcustomercarerecommendations,predictiveanalyticsactsinreal-time,dynamicallyselectingthead,webcontentorcross-sellproducteachvisitorismostlikelytoclickonorrespondto.

PredictiveAnalyticsAppliedisaself-pacedonlinecourseinstructedbythefoundingchairofPredictiveAnalyticsWorldthatcoversthefollowingtopics:

• Applications:Business,marketingandwebproblemssolvedwithpredictiveanalytics.Themanywaysitspredictionscanbeusedtodrivevariousbusinessdecisions.

• Core Technology:Howapredictivemodelworksandhowit’screated.Whatapredictivemodellookslikeunderthecover.Whatdataisrequiredforpredictivemodeling.

• Evaluation:Howwellapredictivemodelworksandhowmuchrevenueitgenerates.

• Management:Projectleadershipandbusinessprocessforpredictiveanalytics;theorganizationalchallengesandhowtoovercomethem.

• Illustrations:Livedemosanddetailedcasestudies.

• Hands-on:“Getyourhandsdirty”witharevealingExcel-basedexercise,bringingapredictivemodeltolifeandseeingitimprovebeforeyoureyes.

System requirements to view this online training program:• High-speedInternetconnection

• AdobeFlashPlayer9installed

You will receive access to the online training program by way of an email sent within two business days of registration. (please check your SPAM folder if you do not see the message within two business days)

knowledge level: Nobackgroundinstatisticsormodelingisrequired.TheonlyspecificknowledgeassumedforthistrainingprogramismoderateexperiencewithMicrosoftExcelorequivalent.

To get more information or to register for this course, go to:www.predictiveanalyticsworld.com/sanfrancisco/2013/intro_online_workshop.php


Featured Speakers & keynote Bios

Rayid GhaniChief Data ScientistObama for America

Rayid Ghani was the Chief Scientist at Obama for America 2012 campaign focusing on analytics, technology, and data. His work focused on improving different functions of the cam-paign including fundraising, volunteer, and voter targeting and mobilization using analytics, social media, and machine learning. Before joining the campaign, Rayid was a Senior Re-search Scientist and Director of Analytics research at Accen-ture labs where he led a technology research team focused on applied R&D in analytics, machine learning, and data mining for large-scale & emerging business problems in various indus-tries including healthcare, retail & CPG, manufacturing, intel-ligence, and financial services. In addition, Rayid serves as an adviser to several start-ups in Analytics, is an active organizer of and participant in academic and industry analytics confer-ences, and publishes regularly in machine learning and data mining conferences and journals.

Keynote: Analytics and the Presidential Elections

Anthony GoldbloomFounder & CEOkaggle

Anthony Goldbloom is the founder and CEO of Kaggle, the leading platform for data prediction competitions that allows organizations to post their data and have it scrutinized by the world’s best data scientists. In 2011, Forbes Magazine cited An-thony as one of the 30 under 30 in technology and Fast Com-pany featured him as one of the innovative thinkers who are changing the future of business.

Keynote: The $3m Heritage Health Prize: Results and Conclusions

Edward NazarkoClient Technical AdvisorIBM

Ed nazarko is an IBM Client Technical Advisor who works with healthcare payers on applying innovative technologies to solve customer problems, and industry problems. His focus is on

combining technology innovation with customer-focused busi-ness and operations strategy. Recent projects have included performance engineering of large systems, application of com-binatorial test design to optimization of ICD-10 test cases, cre-ation of benefit rule abstraction and change validation tools, and traditional system design and build. As a consultant he has worked with pharmaceutical, device, healthcare delivery, and health insurers on a wide range of operational and strategic technology issues. He has also been in startups in life scienc-es, e-business and research. Ed has a BA from Reed College in Portland OR and an MBA from Boston University.

Keynote: Putting IBM Watson to Work

Dr. John ElderCEO & FounderElder Research, Inc.

Dr. John Elder heads the US’s leading data mining consulting team -- with offices in Charlottesville virginia, Washington DC, Baltimore Maryland, and Manhasset new York. Founded in 1995, Elder Research (www.datamininglab.com) focuses on investment, commercial and security applications of advanced analytics, including text mining, credit scoring, image recogni-tion, process optimization, cross-selling, drug efficacy, market timing, and fraud detection.

John obtained a BS and MEE in Electrical Engineering from Rice University, and a PhD in Systems Engineering from the Univer-sity of virginia, where he’s an adjunct professor teaching Op-timization or Data Mining. Prior to 17 years at ERI, he spent 5 years in aerospace defense consulting, 4 heading research at an investment management firm, and 2 in Rice’s Computa-tional & Applied Mathematics department.

Dr. Elder has authored innovative data mining tools, is a fre-quent keynote speaker, and was co-chair of the 2009 Knowl-edge Discovery and Data Mining conference, in Paris. John was honored to serve for 5 years on a panel appointed by President Bush to guide technology for national Security. His book with Bob nisbet and Gary Miner, Handbook of Statistical Analysis & Data Mining Applications, won the PROSE award for Math-ematics in 2009. His book with Giovanni Seni, Ensemble Meth-ods in Data Mining, was published in February 2010, and his book with colleague Dr. Andrew Fast and 4 others on Practical Text Mining was published in January 2012.

John is honored to be a follower of Christ and father of 5.

Special Plenary Session: General Lessons We Can Learn from Blackbox Trading

For more speaker bios, please visit: www.predictiveanalyticsworld.com/sanfrancisco/2013/speakers.php


Exhibitor Floorplan

120

123 222 224 223 322 324 323 422 424 423 522 524 523 622 624 623

720

718

716

714612

115

T4 T2

T3 T1

P15

ENTRANCE

P5

212

113 712

710

708

706

704

702

700

118

116

114

112

110

108

106

104

102

100

107

101 201 301 401 501 600

606 607

601

P14 P4

P13 P3

P12 P2

P11 P1

Absolutdata Technologies, Inc. ....................... 606Act-On Software ............................................... 100Actuate ............................................................. P12Alpine Data labs .............................................. 110Anametrix ......................................................... 524ClickTale ............................................................ 424comScore ........................................................... 622Connectleader ................................................. 116Couch & Associates ........................................... 401DAA ................................................................... 714Deloitte Global Services ................................... 612DMAnC ............................................................... T3Ensighten .......................................................... 700ExactTarget ....................................................... 113Foresee .............................................................. 301Forio Online Simulations ................................. 422Genpact ............................................................. 118High Impact Prospecting .................................. 115iDashboards ...................................................... P11IIA ........................................................................ T1Impact Radius ................................................... P13

Inbenta .............................................................. 708Information Builders ........................................ 108Inkiru ................................................................. 212Insideview ........................................................ 704iPerceptions ...................................................... 123Kapost ................................................................. T4KxEn ................................................................. P15latentview Analytics ........................................ 624lead Converter ................................................. 104localytics ............................................................. P2Majestic SEO ..................................................... 322Marchex ............................................................ 423Mastercard ........................................................ 106neustar AdAdvisor ............................................. P3numeric Staffing Services .................................. P1Opinionlab ....................................................... 107Optimizely ........................................................ 706Oxdata Inc. ........................................................ 222Racom Communications .................................. 114Recommind ....................................................... 522Revolution Analytics ........................................ 323

Rise Interactive ................................................. 501Sales Assoiate .................................................... T2Salford ............................................................... 716SAP Global Marketing, Inc. .............................. 101Search Mojo ...................................................... 702Sitespect ............................................................ 523SiteTuners ......................................................... 607Social 123 .......................................................... 718Splunk ............................................................... 223StatSoft ............................................................. 201Tableau ............................................................... P5Tealium ............................................................. 600Turing Data ......................................................... P4UBC .................................................................... 712

UC San Diego Extension ................................... 710

University of California, Irvine Extension ....... 324

University of San Francisco, Master of Science in Analytics ......................... 224UserTesting ....................................................... 120vorsight............................................................. 116Webtrends ........................................................ 601


Thank you To Our Sponsors

DIAMOnD SPOnSORS

PlATInUM SPOnSOR GOlD SPOnSORS

SIlvER SPOnSORS

BROnZE SPOnSORS

TURnKEY PODS

AUTHOR’S TABlE SPOnSOR lUnCH & lEARn SPOnSOR

ASSOCIATIOn PARTnERS MEDIA PARTnERS


Sponsor Profiles

Diamond Sponsors

ForeSee www.foresee.comBooth: 301

As a pioneer in customer experience analytics, ForeSee continuously measures satisfaction across customer touch points and delivers critical insights on where to prioritize improvements for maximum impact. Because ForeSee’s superior technology and proven methodol-ogy connect the customer experience to the bottom line, executives and managers are able to drive future success by confidently optimizing the efforts that will achieve business and brand objectives. The result is bet-ter business for companies and a better experience for consumers. visit us at www.ForeSee.com for customer experience solutions and original research.

SAP www.sap.comBooth: 101

As market leader in enterprise application software, SAP helps companies of all sizes and industries run better. From back office to boardroom, warehouse to storefront, desktop to mobile device – SAP empowers people and organizations to work together more effi-ciently and use business insight more effectively to stay ahead of the competition. SAP applications and ser-vices enable more than 197,000 customers to operate profitably, adapt continuously, and grow sustainably.

Platinum Sponsor

Deloitte www.deloitte.comBooth: 612

About Deloitte’s Analytics Approach.

An organisation’s data is full of potential. Stored throughout the business, it has a wealth of possibili-ties. leading businesses recognise that a better un-derstanding of data (particularly as a predictor of the future or as an identifier of existing issues) can create

new opportunities and make a significant difference to managing performance. Analytics is, in our opinion, the natural evolution of business intelligence process-es, tools and technologies. While business intelligence focuses on historical analysis, analytics builds upon this set of technologies and techniques to re-focus on the future; helping predict future trends, opportunities and threats.

Deloitte’s deep industry expertise and advanced analyt-ics capability can help decision-makers to maximise the value of their data. By looking at an organisation from the inside out we can turn everyday information into useful and actionable insights. Deloitte is one of the world’s leading professional services firms, providing audit, tax, consulting, and financial advisory services to public and private clients spanning multiple industries. With a globally connected network of member firms in more than 140 countries, we bring world-class capabili-ties and deep local expertise to help clients succeed wherever they operate. Our 170,000 professionals are committed to becoming the standard of excellence.

Gold Sponsor

AbsolutData www.absolutdata.comBooth: 606

AbsolutData Holdings Inc., is a global leader in apply-ing analytics to drive sales and increase profits for its customers. AbsolutData has built strong traction with Fortune 1000 companies across 40 countries. The com-pany specializes in big data, high end business analyt-ics, predictive modelling, reporting and data manage-ment services. These services provide significant value to clients by helping them optimize marketing spends, undertake targeted marketing, and using customer relationship analytics to achieve superior retention and cross sell.

The company is investing in emerging areas such as big data, web and social media analytics. It currently em-ploys 275 professionals across offices in San Francisco, los Angeles, new York, Chicago and Gurgaon.


Inkiru www.inkiru.comBooth: 212

The Inkiru Predictive Intelligence™ platform hosts a variety of real-time, transaction-oriented predictive models. The SaaS-based platform provides an end-to-end solution for data scientists – support for SAS and R, a real-time decision engine, data augmentation, dash-boards and monitoring, and an analytics sandbox. The customized models can address many customer interac-tion challenges — increasing new customer activation, improving conversions, optimizing campaigns for tar-geting, reducing fraud – and run in real-time, utilizing always-current information from our Predictive Graph. The holistic view we create of each customer results in extremely accurate scores and recommendations that adapt in real-time as patterns and trends change.

StatSoft www.statsoft.com Booth: 201

StatSoft, Inc., founded in 1984, is one of the largest global producers of enterprise and desktop software for Predictive Analytics, Text/Data Mining, Quality Con-trol, Web-based Analytics, and Business Decisioning. Our highly scalable STATISTICA Enterprise™ is preferred across a variety of industries in mission-critical appli-cations wherever predictive modeling helps increase productivity, control risk, reduce waste, protect the environment, and streamline operations. StatSoft sup-portsSTATISTICA installations with training and consult-ing through 30 offices worldwide.

Silver Sponsors

Alpine Data Labs www.alpinedatalabs.com Booth: 110

Alpine Data labs is the leader in data science for Ha-doop and big data. The company’s products uniquely combine intuitive interfaces, native analytic processing

in Hadoop, high performance in-database analytics, and the efficiencies of cloud computing to define the new paradigm in advanced analytics: accessible, easy to use, and built for big data. Alpine’s solutions enable data experts and novices alike to work across organiza-tional barriers and collaboratively realize the predictive power of big data analytics. For more information visit www.alpinedatalabs.com.

ExactTarget www.exacttarget.comBooth: 113ExactTarget is a leading global provider of cross-channel digi-tal marketing software-as-a-service solutions that empower organizations of all sizes to communicate with their custom-ers through email, mobile, social media, Web and marketing automation. ExactTarget’s suite of integrated applications enable marketers to drive customer engagement, increase sales and improve return on marketing investment. Headquartered in Indianapolis, Indiana with offices in north America, Europe, South America and Australia, ExactTarget trades on the new York Stock Exchange under the ticker symbol “ET.”

Recommind www.recommind.com Booth: 522

Recommind is the global leader in unstructured infor-mation management and analysis software, delivering business applications that transform the way organiza-tions find, manage, analyze and act upon large vol-umes of electronic information.

Revolution Analytics www.revolutionanalytics.com Booth: 323

Revolution Analytics delivers advanced analytics soft-ware at half the cost of existing solutions. By building on open source R—the world’s most powerful statis-tics software—with innovations in big data analysis, integration and user experience, Revolution Analytics meets the demands and requirements of modern data-driven businesses.

Sponsor Profiles


Bronze SponsorsForio www.forio.com Booth: 422

Put interactive analyses in the hands of decision-mak-ers: create analytic applications that let users change assumptions and see results through their browsers. With Forio Analytics Platform, develop models in Julia (a new, high-performance computing language with capabilities similar to R and MATlAB) or other lan-guages, import Excel data and enable users to share and compare scenarios online. Forio Analytics Platform combines sophisticated analysis, universally accessible online data visualizations, and a centralized model with secure access.

Information Builders www.informationbuilders.comBooth: 108

Information Builders helps organizations transform data into business value. Our software solutions for business intelligence and analytics, integration, and data integrity empower people to make smarter deci-sions, strengthen customer relationships, and drive growth. Our dedication to customer success is un-matched in the industry. visit informationbuilders.com and follow @infobldrs on Twitter.

LatentView www.latentview.comBooth: 624

latentview provides knowledge services focused on data analysis and insights that helps with decisions around marketing, risk and customer management for consumer intensive businesses. For a typical enterprise client, latentview sets up dedicated offshore Analytics Centers of Excellence that assist with targeted cus-tomer acquisitions, enhancing channel effectiveness, understanding customer segments, and developing data-driven campaigns. We blend our business knowl-edge, expertise in quantitative methods, and data management to provide a complete solution.

H2O www.0xdata.comBooth: 222

H2O is an extensible statistical and machine learning platform for math on BigData. H2O gives approxi-mate results at each stage of computation for Adhoc analytics and Data Munging at scale via familiar R-like workflows. It is easy to install into the hadoop and R environments & integrates via JSOn into business ap-plications. 0xdata makes H2O.

Salford Systems www.salford-systems.comBooth: 716

Salford Systems is an award-winning predictive ana-lytics software development and consulting company with a proven record of technical and practical ex-cellence. Our technology accelerates the process of model building by conducting substantial portions of the model exploration and refinement process for the analyst. Applications span fraud detection, credit scor-ing, market research segmentation, direct marketing, drug discovery and risk management. Industries using Salford products and services include banking, insur-ance, healthcare, telecommunications, transportation, manufacturing, and education.

University of California, Irvine Extension www.extension.uci.edu/pa Booth: 324

University of California, Irvine Extension offers an on-line Predictive Analytics Certificate Program presented in partnership with Predictive Analytics World. The cur-riculum focuses on developing a comprehensive under-standing of the creation and utilization of Predictive Analytics models by defining business goals, preparing data, developing and verifying a model, then deploy-ing and refining it. To receive the certificate, students must complete five required and three online elective courses.

Sponsor Profiles


UC San Diego Extension www.extension.ucsd.edu Booth: 710

Through cutting-edge certificates and courses, UC San Diego Extension’s professional development programs enhance skill development in critical occupations. With more than 4,900 courses and 30,000 students per year, Extension represents a vibrant nexus of classes and programs attracting both organizations and individu-als alike. Curriculum draws on civic and industry trends while delivering the most recent and applicable knowl-edge. Students gain practical skills, acquire a wider network of peers, and enjoy increased effectiveness in the workplace.

University of San Francisco www.usfca.edu Booth: 224

The University of San Francisco’s School of Manage-ment educates students to build more productive and compassionate organizations. The School of Manage-ment is a catalyst for change in business, government and non-profit managerial practice. Our students are challenged to connect critical thought with purposeful action, to go beyond their rigorous academic curricu-lum to develop ethical management practices. Our students emerge with the desire to change the world and the skills to be able to do so.

Turnkey Pods

Actuate www.actuate.com Booth: P12

Actuate founded and co-leads the Eclipse BIRT (Busi-ness Intelligence and Reporting Tools) open source project. BIRT is the premier development environment

to present data visualizations in compelling ways via the web on any device. Actuate products add interac-tivity, dashboards, analytics, and deployment options for web and mobile applications.

KXEN www.kxen.com Booth: P15

KxEn is revolutionizing the way companies use predic-tive analytics to make better decisions on petabytes of big data. The company’s flagship product, InfiniteIn-sight®, delivers orders of magnitude improvements in speed and agility to optimize every step in the cus-tomer lifecycle– including acquisition, cross-sell, up-sell, retention and next best activity.

Tableau Software www.tableausoftware.com Booth: P5

Tableau Software helps people see and understand data. Used by more than 9,000 organizations world-wide, Tableau’s award-winning software delivers fast analytics and rapid-fire business intelligence. Create visualizations and dashboards in minutes, then share in seconds. The result? You get answers from data quickly, with no programming required.

Turing Data www.turingdata.com Booth: P4

Turing Data provides Data processing, discovery and analysis of consumer behavior, utilizing a unique pat-tern recognition algorithm.

The results are available in Turing Data’s SaaS Web In-terface in an easy to understand but sophisticated data processing, tabulation, and graphics program.

Sponsor Profiles


Author’s Table Sponsor

MasterCard Advisors www.mastercardadvisors.com Booth: 106

MasterCard Advisors provides clients with insights and solutions that drive business impact and ROI. Aggregated, anonymous transaction data from 1.9 billion cards globally and deep industry expertise allows Advisors to deliver consumer insights and a consultative approach that enables decisions at the speed of consumer behavior.

Lunch & Learn Sponsor

Genpact Limited www.genpact.com Booth: 118

Genpact limited (nYSE: G), a global leader in business process management and technology services, lever-ages the power of smarter processes, smarter analytics and smarter technology to help its clients drive intel-ligence across their enterprise. Genpact’s Smart En-terprise Processes (SEPSM) framework combined with industry vertical expertise leads to superior business outcomes. Genpact’s Smart Decision Services deliver valuable business insights through targeted analytics, reengineering expertise, and advanced risk manage-ment. Making technology more intelligent by embed-ding it with process and data insights, Genpact also offers a wide range of technology services. Driven by a passion for process innovation and operational excel-lence built on its Six Sigma DnA and serving GE for 15+ years, the company’s 60,500+ professionals deliver services to its more than 600 clients from a network of 74 delivery centers across 20 countries supporting more than 30 languages. For more information, visit www.genpact.com. Follow Genpact on Twitter, Facebook and linkedIn.

Association Partners

The International Institute for Analytics www.iianalytics.comBooth: T2

IIA is the only research firm dedicated exclusively to the growing analytics industry. Founded on the prem-ise that analytics is the most compelling competitive differentiator in industry today, IIA defines the path to analytical excellence by guiding enterprises on how to best fund, staff, manage, evaluate, and refine their analytics programs.

Our collaborative research approach offers the benefits of a professional association, the inspiration of a face-to-face network, and the reliability of a world-class research library and faculty team. Together, our com-munity heritage drives the highest standards of profes-sional insights and a rigorous commitment to quality research that uncovers actionable, repeatable, and transferable practices for our clients.

The San Francisco Bay Area Chapter of ACM www.sfbayacm.org

The San Francisco Bay Area Chapter of ACM was founded in 1957 and combined with the San Francisco Peninsula Chapter in 1970. This Chapter is organized for the following educational and scientific purposes: to promote an increased knowledge of and greater interest in the science, design, development, construc-tion, languages, management and applications of modern computing; to provide a means of communica-tion between persons having an interest in computing; to cooperate with other professional groups in the presentation of programs of interest to the Chapter.

Sponsor Profiles


The SFBay Chapter meets the third Wednesday of every month – except December. Our Data Mining SIG meets on the fourth Monday of the month. While our talks are free, membership is only $20 per year, so please consider joining. Professional Development Seminars are offered twice a year (schedule and location vary).

San Francisco Bay Area Interactive Groupwww.sfbig.org

San Francisco Bay Area Interactive Group (sfBIG) is a non-profit professional association dedicated to cham-pioning innovation in digital marketing to brand mar-keters, publishers and agencies through educational networking, and association events.

Media Partners

CustomerThink www.customerthink.com

CustomerThink is a global online community of busi-ness leaders striving to create profitable customer-centric enterprises. Each month, the site reaches over 200,000 subscribers and visitors from 200 countries via email, RSS, linkedIn and Twitter. CustomerThink cur-rently serves over 80,000 visitors per month. Our main areas of coverage are Customer Relationship Manage-ment, Customer Experience Management and Social Business. This is the place to learn about every facet of customer-centric business management in articles, blogs, interviews, and news.

Data Science Central www.datasciencecentral.com

Data Science Central is an online resource for Big Data Practitioners. Featuring news, commentary, and social networking, DSC covers analytics, visualization, integra-tion, tools and trends, and also provides an outlet for career opportunities.

IT Briefcase www.itbriefcase.net

IT Briefcase is a focused online publication that attracts business and IT professionals who are actively research-ing business integration solutions.

Our growing audience can expect to view the most up to date industry news, articles, whitepapers, webcasts, and blogs in additional to IT Briefcase original editorial content showcased in the “Fresh Ink” and “IT Analyst Blog” sections of our website. Some of the topics we cover include Data and Analytics, Cloud Computing, Application Integration, Health IT and Open Source.

KDnuggets www.kdnuggets.com

KDnuggets, Data Mining Community’s Top Resource for Data Mining and Analytics news, Software, Jobs, Consulting, and more.

Smart Data Collective www.smartdatacollective.com

Smart Data Collective is a curated writer’s forum and discussion site published by Social Media Today llC. We cover business intelligence, data analytics, risk manage-ment and related topics for an audience of business leaders and IT experts. In addition to our regular blog coverage, we also produce webinars, e-books, moder-ated Tweet chats and other forms of digital content. We provide a platform for recognized, global authori-ties to share their insights about Big Data. Smart Data Collective is a rich resource for executives who seek cutting-edge analysis of the accelerating growth of data in our interconnected world.

Sponsor Profiles


Notes

EVENTS CALENDAR

www.risingmedia.com

www.emetrics.org

Chicago - June 10-13, 2013Sydney - June 25-26, 2013Boston - Sept 29 - Oct 3, 2013Stockholm - October 14-15, 2013London - October 23-24, 2013Berlin - November 4-5, 2013........................

www.predictiveanalyticsworld.com

Chicago - June 10-13, 2013PAWGOV September 18-19, 2013Boston - Sept 29 - Oct 3, 2013London - October 23-24, 2013Berlin - November 4-5, 2013........................

www.textanalyticsworld.com

Boston - October 2-4, 2013........................

www.conversionconference.com

Paris - June 6, 2013Chicago - June 10-13, 2013Boston - Sept 29 - Oct 3, 2013London - October 23-24, 2013Berlin - November 4-5, 2013........................

www.integratedmarketingsummit.com

Chicago - June 10-13, 2013

www.affiliatemanagementdays.com

London - May 15-16, 2013

........................

www.admonstersops.co.uk

London - April 23, 2013Berlin - June 02-04, 2013November 22, 2013

........................

www.buildingbusinesscapability.com

Sydney - September 9-12, 2013Las Vegas - November 11-15, 2013

........................

www.searchmarketingexpo.com

London - May 14-16, 2013Paris - June 6-7, 2013Stockholm - October 14-15, 2013

........................

www.semtechbizsf2013.semanticweb.com

Berlin - September 2013

........................

www.socialmediaeconomy.de

Munich - November 11-12, 2013

www.socialgamingsummit.de

Berlin - May 14-15, 2013London - November 21, 2013

........................

www.devcon.allfacebook.de

Berlin - November 2013

........................

www.marketingcon.allfacebook.de

Munich - April 29, 2013Berlin - November 2013

.......................

www.semphonic.com/x-change/europe

Berlin - June 11-12, 2013

........................

www.webeffectivenessconference.com

Europe - June 5-6, 2013USA - September 2014

.......................

www.contextconference.comChicago- June 11-13, 2013

Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee, and its network of member firms, each of which is a legally separate and independent entity. Please see www.deloitte.com/about for a detailed description of the legal structure of Deloitte Touche Tohmatsu Limited and its member firms.

© 2012 Deloitte Global Services Limited

You know your organization’s data is full of potential. Stored and siloed throughout your business, it represents a wealth of possibilities. Deloitte’s deep industry experience and advanced analytics capability maximizes the value of data. We look at an organization from the inside out – turning everyday information into useful and actionable insights that inform your decision-making.

www.deloitteanalytics.com

Your dataInside out

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