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Big Data InnovationAchieving Greater Insight through Big Data

September 12 & 13, 2013Westin Copley Place | Boston, MA

Confirmed Speakers

• BI Engineer, Facebook

• Senior Research Scientist, Thomson Reuters

• VP, Surveillance Analytics, Goldman Sachs• Lead Engineer, Orbitz Worldwide

• Sr Manager, Product Intelligence, Salesforce• Senior Data Scientist, LinkedIn

• Senior Scientist, John Hopkins University

• Engineering Manager, Twitter• Head of Merchandising Insights, Nokia

• Marketing Decision Scientist, Dell• Manager, Analytics, Paychex

• Chief Data Scientist, Hopper

• Data Scientist, NASA Tournament Lab at Harvard• Technical Program Manager, LinkedIn

• Data Scientist, PayPal

• Principal Data Scientist, Gilt Groupe• Architecture & Big Data, Cardinal Health

• Director, Media Technology Services, NBC Universal• Cloud Platform Architect, Netflix

• Senior Data Scientist, Zions Bancorporation

• Former VP, Engineering & Advisor, Klout• Sr Enterprise Architect, Citi

• Data Scientist, Twitter

Confirmed Speakers• Chief Data Officer, Express Scripts

• Leader, Data Science Group, NASA• Distinguished Architect, WalmartLabs

• Co-Creator, Apache Hive• Big Data & Analytics Lead, AT&T

• BI Architect, Move.com

• Director, Strategy & Analytics, GE Energy• Lead Technologist, Boeing

• VP, Data & Analytics, Salesforce

• Chief Architect, StubHub• Director, Big Data Platform, PayPal

• Data Architect, Choice Hotels• Sr Manager, Hadoop Infrastructure, Sears

• Platform Engineer, Netflix

• Former Deputy CAO, Obama for America• Director, Engineering, FindTheBest

• Software Architect, LinkedIn• Chief Data Scientist, Mailchimp

• Data Scientist, Zions Bancorporation

• Architect, Quintiles• Director, Architect for Analytics, Autotrader.com

• Data Scientist, Salesforce• Chief Operating Officer, Gui.de

Past Delegates include

• Director, Big Data - Nokia

• Director, Enterprise Data - Capital One

• Vice President - Google

• Senior Director - Starbucks

• Director, Engineering - Coca-Cola

• Director, Insight - EA Electronic Arts

Who Will You Meet?There is no question that IE. provides the gold standard events in the industry and will connect you with decision makers within the Big Data space. You will be meeting senior level executives from major corporations and innovative small to medium size companies.

Job Title Of Attendees

President/Principal

SVP/VP

C-Level

Snr. Director/Director

Global Head/ Head

Snr. Manager/Manager

Academic (1%)

78%

1000+ Employees300-999 Employees50-299 EmployeesLess than 49 Employees

Company Size Of Attendees

8%

11%

25%56% 81%Attendees are

companies with at least 300

employees

3%

21%

12%

42%

13%

8%

Attendees are at Director level or above

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The Big Data Innovation Summit brings together thought-leaders from the industry for an event acclaimed for its interactive sessions and high-level speakers.

As many organizat ions are now work ing with unmanageably large data sets, the importance of using and maintaining an analytics platform which can cope with this scale of information is essential. This presents both a challenge and opportunity as organizations must identify patterns and gain actionable results in order to gain a crucial advantage over competitors.

Illustrated intermittently with case studies, interactive panel sessions and deep-dive discussions, this summit

offers solutions and insight from the leaders operating in the Big Data space.

Big Data Innovation will help your business understand & utilize data-driven strategies and discover what disciplines will change because of the advent of data. With a vast amount of data now available, modern businesses are faced with the challenge of storage, management, analysis, visualization, security and disruptive tools & technologies.

About The Summit

Speaker Information

Digvijay Lamba leads the social platform effort for @WalmartLabs, Walmart’s hub for technology innovation in the areas of social, mobile and retail for the next-generation of e-commerce. Digvijay joined Walmart through its acquisition of Kosmix in 2011. He brings many years of experience in designing Search, Data Mining, and Big Data Systems to @WalmartLabs. In 2007, Digvijay joined Kosmix where he oversaw the development of the Kosmix categorization system and the underlying Data Mining and Big Data technologies that powered Kosmix’s topical search engines. Prior to Kosmix, Digvijay led the search and data team at Andale, a leading provider of vendor solutions for eBay Sellers, where he managed the development of Andale’s data research products.

Building a System for Discovering Unexpected Insights

One of the key benefits of Big Data technologies is to find insights without having to know the right questions to ask. Typically, this requires data analysts with domain knowledge to experiment with the data. At @WalmartLabs, we are working on automating the discovery of interesting and unexpected insights that are relevant to a wide variety of business stakeholders. Can we discover the next trend in food or electronics before it becomes popular? How do we build a system that monitors data for the unexpected? What do we do with the data to make it meaningful for consumers?

Digvijay LambaDistinguished ArchitectWalmartLabs

Dmitriy Ryaboy (@squarecog) leads Twitter’s Analytics Infrastructure team, responsible for growing Twitter's analytics platform from a few dozen Hadoop nodes in 2010 to thousands of machines, multiple clusters and data processing frameworks, and hundreds of diverse use

cases in 2013. He is a contributor to several open-source projects, including Twitter's Elephant-Bird library, Apache Pig, and the columnar storage format Parquet.   His past employers include Cloudera, Ask.com, and Lawrence Berkeley National Laboratory. He holds degrees from Carnegie Mellon University and UC Berkeley.

Dmitiry RyaboyEngineering ManagerTwitter

Tom Noda is a lead engineer at Orbitz Worldwide. He focuses on research and development for next generation of online travel applications to leverage machine learning and massive amount of travel data to help travelers make better decisions. Some of the research areas are flight/hotel price prediction, user review analysis, hotel recommender system, and macro travel trends. Prior to his current role, Tom had been designing and developing large-scale auto bidding system for search engine marketing using Hadoop and HBase. He holds B.S. and M.S. in Industrial Engineering from University of Wisconsin - Madison.

Hotel Recommender System

Imagine there is a traveler who stayed at the Four Seasons in NY and another who stayed at the Holiday Inn Express in LA. Which hotels would you recommend if both are preparing for the next trip to Chicago? Traditionally, hotel recommender systems have been built around content based filtering, using hotel star ratings, locations, amenities, and prices. In this session, we’d like to share our “collaborative filtering” approach (i.e. neighborhood method, matrix factorization) and see how travelers have similar “tastes” about hotels. For optimization/minimization, we are using Hadoop MapReduce to parallelize computations of millions of user data and hundreds of thousands of hotels.

Tom NodaLead EngineerOrbitz Worldwide

Integrated Framework for Detecting Insider Trading Fraud

The talk will discuss how big data can be leveraged to create an integrated framework to detect fraud and explain it in an insider trading context. A distinct component is used to identify opportunity, actor behavior and actor relationships. Actor relationships are identified through a social network analysis ( SNA )

model. This can be based on internal data from email, IM, proximity, phone logs, HR and CRM systems. The other components being a behavior model to identify change in actor behavior or identify repetitive behavior. The last component is to identify opportunity for trading fraud. News Analytics leverages unstructured data to identify corporate events and are combined with Market movement to identify opportunity. We wrap with a short discussion on how this can be extended to identify suspic ious communication leveraging text analytics.

Punit MahajanVice President, Surveillance AnalyticsGoldman Sachs

Nikunj Oza is the leader of the Data Sciences Group at NASA Ames Research Center and the Discovery of Precursors to Safety Incidents (DPSI) team which applies data mining to aviation safety. Dr. Oza’s 40+ research papers represent his research interests which include data mining, fault detection, and their applications to Aeronautics and Earth Science. He received the Arch T. Colwell Award for co-authoring one of the five most innovative technical papers selected from 3300+ SAE technical papers in 2005. He received his B.S. in Mathematics with Computer Science from MIT in 1994, and M.S. (in 1998) and Ph.D. (in 2001) in Computer Science from the University of California at Berkeley.

Big Data Innovations and Applications at NASA

This presentation will discuss problems of interest to NASA in aeronautics, space exploration, and Earth science that involve big data. We will discuss the nature of the big data (they are not just big, but difficult!), the innovations that the Data Sciences Group has developed to target different components of these problems, and how these innovations have been deployed to help solve these problems. Many of our algorithms have been open-sourced, and we will show how you can join our community of users and developers.

Nikunj OzaLeader, Data Sciences GroupNASA

Hien Luu is a senior member of the Data Services Platform team at LinkedIn and he is the technical lead of the LinkedIn Member Segmentation platform.   He enjoys teaching and is currently an instructor of the Hadoop: Big Data Processing course at UCSC Silicon Valley Extension school. He has given presentations at various conferences and user groups like JavaOne, Silicon Valley CodeCamp and SVForm Software & Architecture user group.   He loves working with big data technologies and recently became a contributor of Apache Pig project.

LinkedIn Segmentation and Targeting Platform: A Big Data Application

Creating member segmentations is a primary function of the marketing team at an internet company. Marketing teams are constantly creating various member segments tailored to the needs of marketing campaigns, and these needs are changing frequently. Because of this, there is a huge need for a self-service member segmentation platform that is easy to use and scalable to support large member data sets. This presentation provides details about the architecture of the LinkedIn Member Segmentation platform, and how it leverages Hadoop technologies such as Apache Pig, Apache Hive, and an enterprise data warehouse system such as Teradata, to provide a self-service way to create and manage member segmentations. 

Hien LuSoftware ArchitectLinkedIn

Ivan Bercovich is the Director of Engineering at FindTheBest. Originally from San Juan, Argentina, Ivan moved to the United States to attend the University of Massachusetts Amherst, where he studied electrical engineering and mathematics. He graduated  summa cum laude   from the university and relocated to Silicon Valley to work at Cisco Systems. He soon realized, however, that there was no point to living in California unless he was by the beach, so he headed to Santa Barbara to join FindTheBest. When he’s not trying to conquer the world, Ivan can be found rock climbing, hiking, or doing various other outdoor activities. He also enjoys participating in miscellaneous office debates and shamelessly presenting his guesses as “facts.” 

Big Data for the Little Guy

Many technologies—including personal computers and smartphones—were first developed for businesses, only later becoming the big consumer hits they are now. Today, businesses use Big Data to reduce cost, increase revenue, and improve customer satisfaction. But what a b o u t c o n s u m e r s ? Q u i e t l y , B i g D a t a i s becoming increasingly popular in the consumer market. Sites like Edmunds, Zillow, Kayak, and LinkedIn have begun presenting vast   amounts of   data on specific, consumer-friendly topics. Now, FindTheBest is taking a Big Data approach for the little guy a step further by empowering consumers to make more informed decisions on just about anything.   The company covers a wide array of topics with hundreds of consumer-o r i e n t e d c o m p a r i s o n s , f r o m c o l l e g e s to investment advisors to laptops and much more.

Ivan BercovichDirector, EngineeringFindTheBest

Joe Cline is a fifteen year IT veteran, spending most of his career in the area of data management.   He currently works as a Data Modeler/Architect in Enterprise Information Management at Choice Hotels International. When Joe is not working, he enjoys practicing his new hobby of data science competitions and spending time with his wife Jenn and three dogs, Lia, Maggie and Bear.   You can follow Joe on Twitter @JosCline.

Information Quality Analytics for Big Data with Python

In this presentation, Joe will discuss the importance of IQA and demo analysis techniques with Python to uncover and resolve data quality issues.

Joe ClineBI ArchitectChoice Hotels International

Sastry is Chief Architect at StubHub, responsible for the overall technology architecture, strategy and direction.   This includes both platform and application architecture, service orientation, domain modeling, content management, information discovery, big data platform and enterprise architecture. Sastry works with and leads a team of architects and closely collaborates with product management, engineering and business leads. Sastry is a veteran technologist with nearly two and half decades of experience developing, leading and architecting various highly scalable   and distributed systems, in the areas of Service Oriented Architecture (SOA), Application Servers, Java/J2EE/Web Services middleware, and cloud Computing to name a few. His experience ranges from low level device drivers, which he started with, to operating systems, middleware, application and enterprise architecture, and so on. Before transitioning to StubHub, he led the architecture t r a n s fo r m a t i o n o f e B a y f ro m i t s m o n o l i t h i c architecture to the distributed, and scalable service oriented architecture that it is today. He spearheaded the open source initiative at eBay by creating

eBayopensource.org. Prior to joining eBay, Sastry was co-founder and CTO of OpenGridSolutions, Founding member and Architect at SpikeSource, and an architect at Oracle. Sastry also worked at many other companies in the early stages of his career and holds a Masters degree from I.I.T, Kharagpur, India. Sastry frequently speaks at conferences including JavaOne, Oracle Wor ld , SOA wor ld , QCon and OSCON. Sastry contributed to and represented in many standards evolution at OMG, JCP, GGF and OASIS.

Big Data Platform at the Worlds's Largest Fan-to-Fan Ticket Marketplace

StubHub is the world's largest secondary online ticket marketplace serving millions of users and is on course to transforming itself into the source fans rely on to discover, access and share entertainment experiences worldwide. In order to achieve that, we need a comprehensive big data platform to handle a variety of data sources, data types and use cases, including, but not limited to, personalized recommendations and  analytics. We use a hybrid data platform that employs a traditional data warehouse as well as a Hadoop based platform. This session will describe our use cases, challenges we face and the approach that we took to address these.

Sastry MalladiChief ArchitectStubHub

Dr. Sameena Shah leads Thomson Reuters R&D's work in finding alpha from underexploited data sources. Sameena has been leveraging big data analytics for finding predictive signals from textual information in corporate fil ings, news, social media, company hierarchy analysis etc. Prior to joining Thomson Reuters, she worked for a hedge fund in NYC creating statistical arbitrage driven quantitative strategies. Sameena holds a PhD in Machine Learning and Optimization from IIT Delhi. Her research has received several awards including those from Microsoft Research and Google. Sameena is on the review panel of several major journals and a PC member for several International Conferences. 

Big Data & Quantative Finance

In this talk, Dr. Shah will talk about how their team extracted informative content from textual information present in corporate filings to create a quantitative strategy generating an alpha signal. They processed 3TB of textual information on a Hadoop cluster to generate statistical language models of corporate filings. On a stand alone PC, this would take them weeks to accomplish the task that was completed on Hadoop in under 20 minutes. Sameena will talk about how they generated a ‘conformity score’ for each section in each   filing   that was representative of the distance of the language (or topic) of a particular section from the distribution of scores across a reference set. This allowed them to distinguish sections that are far from the language model distribution as having atypical language vs.   typical language. They   report significant returns can be reaped on shorting companies with extreme atypical language. 

Dr. Sameena ShahSenior Research ScientistThomson Reuters

Vitaly Gordon is a senior data scientist on the LinkedIn Product Data Science team where he develops data products that most of you use every day. Prior to LinkedIn, Vitaly founded the data science team at LivePerson and worked in the elite 8200 unit (the Israeli equivalent of the NSA), leading a team of researchers in developing algorithms to f ight terrorism. His contributions have been recognized through a number of awards including the “Life Source” award, an award given each year deemed most high-impact in saving lives. Vitaly holds a B.Sc in Computer Science and an MBA from the Israeli Institute of Technology.

Patrick Philips is a Technical Program Manager on the Data Science team at Linkedin where   is responsible for the crowdsourcing platform that trains much of

LinkedIn’s awesome machine learning. Previously, he was an early employee at CrowdFlower, a market leader in enterpr ise crowdsourc ing, where he developed scalable crowdsourcing practices for relevance evaluation of search algorithms. In an earlier life, his work as a financial analyst for environmental litigation nearly led him into law school. Patrick received a B.A. in International Politics and Economics from Middlebury College.

Hacking Data Science

Better data beats better algorithms, but better data can be hard to come by. In this talk, Vitaly Gordon, Senior Data Scientist at LinkedIn, and Patrick Philips, Crowdsourcing Expert at LinkedIn, will show how the LinkedIn data science team hacks data science using soph ist icated data min ing and crowdsourc ing techniques to leverage the data they already have and create the data that's missing.

Vitaly Gordon & Patrick PhilipsSenior Data Scientist & Technical Program ManagerLinkedIn

IT is at an inflection point. Gaining new insights and creating new opportunities with big data analytics is becoming a game changer for a growing number of organizations already competing on information and analytics. At the same time the growing number of analyt ics , enterpr ise and mobi le appl icat ions challenge existing beliefs about scalability, data volumes and storage, and how to deal with data security, privacy and lifecycle management.   IBM has worked with hundreds of clients to identify the highest value use cases and the pitfalls to avoid that ensure your organizatoin is ready for the new era of computing and big data. Learn about the best practices and technology innovations that can help you evolve your existing analytic, application and data center investments to improve customer insight and drive business success.

Are You Ready for the New Era of Computing and Big Data?

Phil Francisco has over 25 years of valuable experience in technology development and global technology marketing. As Vice President of Data Management Products and Strategy, he currently directs the product portfolio and strategy for all database software and PureData system products for the IBM Information Management division. Previously Mr. Francisco was Vice P r e s i d e nt of P ro d u c t M a r k et i n g a n d P ro d u c t Management for the IBM PureData System for Analytics and Netezza products; a role he held both prior and subsequent to the acquisition of Netezza by IBM. Prior to Netezza, he held Vice President of Marketing and Product Management roles at PhotonEx and Lucent Technologies' Optical Networking Group. In addition, he has more than 10 years of experience in software, hardware and systems engineering at AT&T/Lucent Bell Laboratories. Mr. Francisco holds a patent in advanced optical network architectures. He earned his Master's degree in Electrical Engineering from Stanford University and completed the Advanced Management Program at the Fuqua School of Business at Duke University. He received B.S.E. degrees in Electrical Engineering and Computer Science from the Moore School of Electrical Engineering at the University of Pennsylvania.

Phil FranciscoVP, Product Management & MarketingIBM

Dr. Rinat Sergeev is Data Scientist at the Harvard-NASA Tournament Lab (NTL) in Cambridge, MA. NTL was established to explore and utilize crowdsourcing approaches in application to the Big Data challenges, faced by NASA and Government. Rinat received his PhD in Physics at Ioffe Institute in Saint Petersburg, Russia. Following his innate curiosity, he’s pursued challenges in a variety of academic fields, from Quantum Mechanics to Immunology and Epidemiology. His research focus includes conceptual analysis, analytical approaches, and models in multiple areas. Personally, he’s a fan of Math puzzles, strategic games, and politics.

Big Data and Crowdsourcing – Will They Make a Happy Couple?

Predicting earthquakes and searching for the tomb of Genghis Khan. Fueling the International Space Station and packing a knapsack for space travel. Foreseeing atrocity and preventing healthcare fraud. Annotating genetic sequences and training robots. What do all these topics have in common? The answer: Crowdsourcing.These and similar problems have been tackled recently by the NASA Tournament Lab, a business-academic collaboration between NASA, Harvard, and the TopCoder community.Crowdsourcing as innovative approach in the age of Big Data will be addressed during the presentation, from the specifics of selection and preparation of the problem to benefits of crowd sourced solutions.

Rinat SergeevData ScientistNASA Tournament Lab at Harvard

Ms. Zhang works at Nokia as Head of Merchandising Insights. She provides thorough executive analyses, predictive models and recommendations for strategic and operational decisions for Nokia Store & Windows Phone Ecosystem to help developers’ apps visibility & success via strategic merchandising and users’ satisfaction and engagement. Before join Nokia, she was Vice President of Analytics at One to One Global providing analytical consulting to clients including Liberty Mutual, Harvard Executive Education, Nuance etc. Prior that she was Director of Business Intelligence at Monster Worldwide responsible for providing statistical analyses, predictive models and strategy recommendations to support Monster’s product strategy, prospects acquisition, customer retention, profit maximization and site optimization.

Mobile Big Data Insights

Big Data   is the fundamental wealth to a company. This also applies to the mobile app space with billions of downloads. The mobile application space is a lucrative place for companies and developers. Its revenue is predicted to reach $46 billion by 2016, including advertising and other revenue streams. Most businesses, realizing the potential of  mobile apps, maintain them for promotional and marketing purposes. Apps let companies and developers make revenue, especially those apps with lots users positive comments and high rating stars. We have been utilized our Nokia Store and Microsoft Marketplace big data to gain insights from app reviews, build a sentiment index to measure the developer’s product reputation, develop a strategy for responding to negative sentiment to positively impact perception, b u i l d i n g p r e d i c t i v e m o d e l i n g a n d d ev e l o p e r s recommendation engine to merchandise our developers apps to make more developers successful and keep our ecosystem healthy.

Yanling ZhangHead of Merchandising InsightsNokia

Robert N. Bernard is the Lead Technologist of the Strategy and Business Development department in Boeing's Integrated Information Systems division.   In addition, he is the vice-chair of the division's Big Data Council.   For over 20 years, he has been a designer, project manager, and programmer in diverse industries including national security, entertainment, urban and

regional planning, and academia. He has specialized in simulation, forecasting, text analysis, wargaming, computational social science, agent-based modeling, and other predictive analytics.   He has a Bachelor's degree from Princeton University, a Master's degree from the University of Michigan, and spent time at the Santa Fe Institute.

Robert N. BernardLead TechnologistBoeing

Erika P. McBride, CPA, Ed.D.   is   the Risk Analytics Manager at Paychex, Inc. Aligned within the Risk Management team, Erika oversees a team of data-mining and predictive modeling experts, while also facilitating cross-functional, objective teams of peers to assess risk throughout the company, resulting in millions of dollars contributed to the bottom line. Erika joined Paychex in 1997 as an Accountant, and worked her way through the ranks in various leadership capacities in financial and risk management roles. Prior to Paychex, Erika was a staff auditor with a regional public accounting firm, as well as a member of a regional HMO Finance team.   She holds an Ed.D.   in   Executive Leadership from St. John Fisher College in Rochester, NY, an MBA from Rochester Institute of Technology, and a B.S. in Accounting from SUNY Geneseo.   Erika is an adjunct professor in business at St. John Fisher College, a five-time presenter and panelist at Treasury and Risk’s

Alexander Hamilton best practices summit, a presenter at the 2011 RIMS Conference and Exhibition, the 2012 Big Data Innovation Summit, and Predictive Analytics World Conferences in New York, Toronto, and Dusseldorf.

Pulling the Needle from the Haystack

In 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, their retention goals.

Erika McBrideManager, AnalyticsPaychex

Tarush Aggarwal works in the Data Engineering team at Salesforce which works on creating the next gen big data load, compute, store, interact, and BI platforms. He is very interested in analysis and visualization of Log Data. He received his bachelor’s degree in Electrical and

Computer Engineering from Carnegie Mellon University in 2011. He was heavily involved in Research work at the Parallel Data lab working on frameworks based around Indexing and Retrieval of Celestial Objects.

Tarush AggarwalData ScientistSalesforce

Ashish Thusoo is the co-creator of Apache Hive and served as the project's founding Vice President at the Apache Software Foundation. He started his working career as an engineer at Oracle where he contributed heavily to many core components of Oracle RDBMS. Ashish ran the Data Infrastructure team at Facebook, leading the team in the creation of one of the largest data processing and analytics platform in the world - a platform that achieved the bold aim of making data accessible to analysts, engineers and data scientists alike within the company.

Taming Elephants, Bees and Pigs - The Big Data Circus

In Taming Elephants, Bees and Pigs - The Big Data Circus, Apache Hive co-creator and Qubole CEO Ashish Thusoo will discuss the reasons and motivations behind the Big Data revolution and how it has evolved from previous data processing technologies. In the context of his unique experience at Facebook, Ashish will talk about some of the key challenges of scale and the evolutionary paths and techniques that were developed as a result. Finally, he will talk about the future of Big Data and how technology is continuing to simplify the process and become accessible for all.

Ashish ThusooCo-CreatorApache Hive

Dr. Mehmet H. Göker is the Vice President of Data & A n a l y t i c s ( C u s t o m e r a n d S a l e s G row t h ) fo r Salesforce.com. He and his team leverage usage data to analyze adoption patterns and determine ways to help customer get the most of their Salesforce implementation and be more successful. Prior to j o i n i n g S a l e s f o r c e , M e h m e t w a s t h e V P o f Recommender Technologies at Strands and Research Director at PriceWaterhouseCooper’s Center for Advanced Research (CAR). Mehmet holds a Dr.-Ing degree from the University of Darmstadt, Germany. He has published more than 50 scientific papers, two books and edited four special issues of the AI magazine. He has been developing real-world intelligent applications for more than 20 years. 

Aron Clymer runs a team of Data Scientists for Product Intelligence at Salesforce.com. The team engages with product executives to inform key product strategy decisions with data analysis and statistical modeling.Aron   completed his MBA from the Haas School of Business at UC Berkeley in 2008, where he focused his degree on direct marketing, strategy, and entrepreneurship. He has over 7 years of experience in Data Science and BI, and 17 years experience in enterprise software.

Customer Insights + Salesforce.com = LIKE

Salesforce.com is a customer-centric enterprise. We understand that our success is directly tied to the success and loyalty of our customers. Our data-driven approach to customer success is driven by two groups: Product Intelligence and Customer Intelligence. The Product Intelligence team (led by Aron Clymer) applies data science to help drive product strategy so we are sure to  build products that delight customers.The team also manages our  valuable "big data" store of customer behavioral data that fuels our analyses. The Customer Intelligence team (led by Mehmet Goker) utilizes product, behavioral and peer group data to ensure that customers get the most out of their investment. The team monitors customer usage to provide guidance on how to improve adoption, suggest additional training and services, and to improve retention. In this presentation, we will describe how customer behavioral data is used to drive product strategy, give an overview of the Early Warning System as a key component to the company's ability to deliver key support in a   targeted  manner, and CloudPulse: our p lat form to de l iver adopt ion metr ics and recommendations to our customers.

Mehmt Gokar & Aron ClymerVP, Data & Analytics &Director, Product IntelligenceSalesforce

Aaron Caldiero is a Senior Data Scientist in the S e c u r i t y A n a l y t i c s D e p a r t m e n t a t Z i o n s Bancorporation. As a Data Scientist, Aaron performs data mining, statistical modeling, and analytics on Zion’s Security Data Warehouse (Hadoop cluster). Using the tools of Data Science Aaron builds, implements, and maintains risk models for fraud and malware detection. Aaron has over ten years of experience in the Analytics and Financial Services industries. He has a B.S. in Psychology from the University of Utah, and a Graduate Certificate in Applied Statistics from Penn State.

C l a y N o y e s i s a D a t a S c i e n t i s t a t Z i o n s Bancorporation.   His primary responsibilities include Fraud Prevention and Information Security.   Prior to his work at Zions, Clay served as a Captain in the US Air Force and was an F-16 Operations Analyst.   He received   his M.S. in Operations Research from MIT in

2008   and   his B.S. in Operations Research from The United States Air Force Academy in 2006.  His research interests include text analytics, machine learning with large-sca le data , probab i l i s t i c mode l ing , and optimization techniques.

Practical Applications of Data Science for Bank Security

At Zions Bancorporation we apply the tools and techniques of Data Science to many areas of our business. Our main focus has been in the area of Bank Security and Fraud Prevention. In this presentation we will be showcasing real world examples of how we have applied Data Science and Big Data Analytics to various areas of our business. We will take you on our journey from business problems to playing with data, and along the way discover insights, weirdness, and obvious facts. At the end of this journey you should be able to realize how you too can put Big Data to use. Big Data is more than a buzzword. You can actually use the stuff.

Aaron Caldiero & Clay NoyesSenior Data Scientist &Data ScientistZions Bancorporation

Will has worked on the Pentaho BI Suite since 2007, and is the author of Packt Publishing's  Pentaho Reporting 3.5 for Java Developers. Prior to joining Pentaho Will worked at GE Research, on projects ranging from aircraft engine expert systems to medical informatics focused on predicting Alzheimer's progression. In addition to spending time with his wife and two sons, Will is always coming up with ideas to work on in his spare time. One of his favorite hobbies is BattleBricks, a competitive Lego otics group that he started with a group of friends.

Will GormanVice President, EngineeringPentaho

Workshop Information

Addressing Complexity and Resource Challengesin a Big Data Environment

Big data technologies are evolving, but still present a challenge to organizations looking for value from large volumes of disparate data sources.   At the center of these challenges is a lack of skilled resources and time to address new and complex technologies like Hadoop, NoSQL and MapReduce.   In this round table we will discuss strategies for eliminating time and complexity in a big data workflow.

Workshop Leader:

Jae Hyeon Bae develops and manages Netflix's data pipeline. The data pipeline dispatches more than 80 billion messages every day to multiple destinations, including the Hive data warehouse. The data pipeline also supports ingesting, indexing, and querying data in real-time.

Danny Yuan is a cloud system architect in the Platform Engineering Team of Netflix. He leads the effort of building and operating Netflix’s data collection pipeline, as well as the real-time insight project of the Platform Engineering Team. He also built Netflix’s crypto service, which manages all the crypto keys used by Netflix applications in the cloud and serves billions of crypto operations every day.

Real-time Insights into Application Events

Netflix applications generate tens of billions of log events every day, and send them to Hadoop clusters over an efficient data pipeline for later analysis.   Different teams constantly query and process the events using Hive and a number of home-grown systems. That said, developers want to be further empowered. They want to explore their applications' events interactively. They want to identify, analyze, and visualize real-time trends in the events with minimal programming effort. We have built an end-to-end system to address these needs. We will talk about how the design of the system, how it is built and operated, and lessons learned. 

Jae Hyeon Bae & Danny YuanSenior Platform Engineer &Cloud Platform ArchitectNetflix

There are a limited number of places available at each workshop below. Avoid missing out by registering in advance. Email Heather James with the name of the workshop(s) you wish to attend to secure your place.

David is the Chief Technology Officer at Composite Software. As CTO, David works directly with customers to guide their data virtualization strategies as well as with  R&D   to guideComposite’s   technology vision and roadmap.   David joined Composite as VP of Engineering in 2002, and became the CTO in 2006. Before Composite he was a venture capital CTO in residence, the CTO of eStyle, headed software product marketing at NeXT Computer, built program trading systems on Wall Street, and researched natural language processing systems at GE’s Corporate R&D center. David holds a BS in Computer Science from Michigan State University and an MS in Computer Science from Rensselaer Polytechnic Institute.

David BesemerChief Technology OfficerComposite Software

Workshop Information

Break the Big Data Analytics Logjam, Beat Your Competition

We all understand the Big Data and Advanced Analytics opportunity.  But the troubling fact is your analysts spend more than half their time doing nitty-gritty data preparation work that delays business value realization.

- Attend this workshop to discover how to remove the data bottleneck from your big data analytics projects.   

- Learn techniques and easy-to-use tools that let you find, access and combine   data   five times faster than traditional methods.

- See how other organizations beat their competition with more big data analytics sooner.

Workshop Leader:

Krishnan Raman is a Data Scientist at Twitter Observability. Previously he was a Data Scientist at Twitter Revenue, where he worked on Marketplace & Modeling problems pertaining to Twitter's ad platforms - promoted tweets on timeline, promoted accounts etc. He was formerly a Risk Quant at Bank of America, an Associate at Goldman Sachs, and an Engineer at Sun Microsystems. His experience in building the realtime proprietary trading system WebET at GS, and concurrent Scala systems to compute the conditional value at risk of large credit portfolios at BAC have stood him in good stead at the Revenue Quality team at Twitter. His primary tools are Scala, Scalding & a dash of statistics & math. He has graduate degrees in Math, CS, and Mathematical Finance from the University of Chicago.

Krishnan RamanData ScientistTwitter

Programming with Scalding

This is a hands-on coding workshop. We will code up a few Scalding programs in different domains - population demographics, portfolio optimization, traffic patterns. While Scalding looks like a thin Scala API atop Cascading, this appearance is deceptive. The power of Scala combined with the mapping, grouping & joining primitives in Scalding, alongwith the Algebird abstract algebra library, allow for a whole new level of flexibility with big data. Please ensure you have Scala, Scalding installed on your laptop computer if you wish to take this class.

Workshop Leader:

Session types

The Big Data Innovation Summit hosts a selection of session options, within the summit you can mix & match the sessions that are most relevant to your needs - all content will also be made available post-summit subject to the presenters permission.

• Presentations - everything from use cases to the challenges & successes faced by those working in the Big Data space

• Panel Sessions - Interactive panels will allow you intimate access to the thought leaders at the top of their game, allowing extensive Q&A time

• Round Table Discussions - Sit with your peers and discuss the latest innovations, sharing ideas, insights & connecting with those close to you

• Big Questions in Big Data - Exclusive to the Big Data Innovation Summit, this session will be a live interview with audience participation, much like a chat show. Reach leading thought leaders and explore their ideas

• Workshops - Hands on demonstrations of the latest technologies helping to drive the space forward. Solutions & Services for your needs.

• Meet the Speaker - Unprecedented access to those presenters filling the day with knowledge and insights

• Access to all Sponsor Zones - Get the technologies that you need, everything from Hadoop Technologies to Business Intelligence needs, Big Data has it for you

“Connected with the right people...attended some awesome presentations & panel sessions...Big Data Innovation is where you want to be” - Big Data Innovation Summit Attendee

The Information

Silver Pass

$1495Access to all sessions &

networking events

$1295Early Bird Price

(until July 12)

Diamond Pass

$1995Access to all sessions, networking events, annual subscription to IE.

membership & full access to co-located Data Visualization Summit

$1795Early Bird Price

(until July 12)

Gold Pass

$1795Access to all sessions, networking events & annual subscription to IE.

membership

$1595Early Bird Price

(until July 12)

Registration Pricing

Big Data Innovation SummitDate: September 12 & 13, 2013Location: Boston, MassachusettsVenue: Westin Copley Place Accommodation: Online ReservationsTelephone Reservations: +1 800 937 8461 Quote ‘IE Group’

For larger groups or special requests contact Patrick by calling +1 415 992 7632 or email plewis@theiegroup.com* Team discounts are applicable at the point of registration only.

Ways to Register

+1 415 992 7632 +1 323 446 7673 http://analytics.theiegroup.com/bigdata-boston/registration

Group Discount Offers3 Silver Passes: $3000 ($1000 per attendee)5 Silver Passes: $4500 ($900 per attendee)3 Gold Passes: $3900 ($1300 per attendee)5 Gold Passes: $6000 ($1200 per attendee)3 Diamond Passes: $4500 ($1500 per attendee)5 Diamond Passes: $7000 ($1400 per attendee)

Early Bird Prices available until July 12 please see below

One Day, Exhibition Area Only and Live Stream Passes also available - contact Patrick plewis@theiegroup.com for details

NAME OF EACH ATTENDEE

TITLE OF EACH ATTENDEE DEPARTMENT

COMPANY INDUSTRY

ADDRESS CITY

STATE/PROVINCE ZIP/POSTAL CODE COUNTRY

EMAIL OF EACH ATTENDEE BUSINESS PHONE NUMBER

1. Delegate Information...

2. Pass Types...Early Bird Pass Options until July 12, 2013

Early Bird Silver: $1295 Attendees ____ Early Bird Gold: $1595 Attendees ____ Early Bird Diamond: $1795 Attendees ____

Regular Pass Options after July 12, 2013 Silver Pass: $1495 Attendees ____ Gold Pass: $1795 Attendees ____ Diamond Pass: $1995 Attendees ____

Group Discount Pass Options 3 Silver Passes $3000 ($1000 per attendee) 5 Silver Passes $4500 ($900 per attendee) 3 Gold Passes $3900 ($1300 per attendee) 5 Gold Passes $6000 ($1200 per attendee) 3 Diamond Passes $4500 ($1500 per attendee) 5 Diamond Passes $7000 ($1400 per attendee)

For larger groups or special requests contact Patrick Lewis by calling +1 (415) 992 7632 or email plewis@theiegroup.comGroup passes only available when all participants register together.

Pass Descriptions:Silver Pass: Access to all sessions & networking eventsGold Pass: Access to all sessions, networking events & annual subscription to IE. membershipDiamond Pass: Access to all sessions, networking events, annual subscription to IE. membership & Strategic Analysis Report

Check (Make checks payable to The Innovation Enterprise Ltd) Invoice me

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BILLING ADDRESS INDUSTRY

Prices are exclusive of VAT. Places are transferable without any charge to another Summit occurring within 12 months of the original purchase. Team discounts are applicable at the point of registration only. Any cancellations within a group registration will in turn incur an increase in registration fee for the remaining group participants. Cancellations before August 9, 2013 incur an administrative charge of 50%. If you cancel your registration after August 9, 2013 you will be charged the full fee. You must notify The Innovation Enterprise in writing of a cancellation, or you will be charged the full fee. The Innovation Enterprise reserve the right to make changes to the program without notice. NB: FULL PAYMENT MUST BE RECEIVED BEFORE THE EVENT.

Registration FormBig Data Innovation SummitSeptember 12 & 13, 2013 | Westin Copley Place | Boston, MAFor registration or more information on the program, please call Patrick on +1 (415) 992 7632, or fax this registration form to +1 (323) 446 7673

3. Payment Options...

Schedule

Networking Drinks 18.00 - 19.30

September 13

Keynote Presentations 08.30 - 10.30

Coffee Break 10.30 - 11.00

Session Two 11.00 - 13.00

Lunch 13.00 - 14.30

Session Three (All tracks begin) 14.30 - 16.00

Coffee Break 16.00 - 16.30

Session Four 16.30 - 18.00

Day Two

September 12Day One 08.30

10.00

10.30

12.00

13.30

15.00

15.30

17.00

19.00

08.30

10.00

10.30

12.00

13.30

15.00

15.30

Session Five 08.30 - 10.30

Coffee Break 10.30 - 11.00

Session Six (All tracks begin) 11.00 - 12.30

Lunch 12.30 - 14.00

Session Seven 14.00 - 15.30

Departure Coffee 15.30 - 16.00

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Sponsors

For sponsorship information, contact Pip at pcurtis@theiegroup.com F TI L

I N - M E M O RY B I G DATA

TM

Platinum Sponsor Gold Sponsor

Silver Sponsor Silver Sponsor

Gold Sponsor

Sponsors

For sponsorship information, contact Pip at pcurtis@theiegroup.com F TI L

Panel Sponsor

Workshop Sponsor Exhibitor

Workshop Sponsor

Sponsorship opportunities are designed to maximize your ROI.

Customizable packages ensure your company, brand, products and services are promoted to senior decision makers in todays leading industry organizations.

“The people we need to be talking to are here!” - 2012 Sponsor

Contact Pip your dedicated sponsorship representative today.Pip Curtis - pcurtis@theiegroup.com

Panel Sponsor

JanuaryBusiness Analytics Innovation Summit January 30 & 31Las Vegas

AprilPredictive AnalyticsInnovation SummitApril 18 & 19Hong Kong

Social Media & Web Analytics Innovation SummitApril 25 & 26San Francisco

Sentiment Analysis Summit April 25 & 26San Francisco

Predictive Analytics Innovation Summit April 30 & May 1London

Social Media & Web Analytics Innovation SummitApril 30 & May 1London

MarchSports Analytics Innovation SummitMarch 21 & 22London

FebruaryPredictive Analytics Innovation Summit February 20 & 21San Diego

OctoberBig Data & Predictive Analytics Summit October 17 & 18Dublin

NovemberElite Minds in Sports Analytics SummitNovember 6London

Sports TechnologyInnovation Summit November 7 & 8London

Business Intelligence Innovation SummitNovember 14 & 15Chicago

Predictive Analytics Innovation Summit November 14 & 15Chicago

Data Science Leadership Summit November 14 & 15Chicago

DecemberPredictive Analytics in Banking Summit December 5 & 6New York

MayBusiness Intelligence Innovation Summit May 22 & 23Chicago

HR Analytics Innovation May 22 & 23Chicago

Business Analytics Innovation Summit May 22 & 23Chicago

SeptemberSocial Media & Web Analytics Innovation SummitSeptember 12 & 13Boston

Sports Analytics Innovation September 12 & 13Boston

Partnership Opportunities: Pip Curtis | pcurtis@theiegroup.com | +1415 992 5349 Attendee Invitation: Sean Foreman | sforeman@theiegroup.com | +1415 692 5514

Sports Social Media

Retail HR

HealthcareExpected Attendees

BankingFlagship Summit

Analytics 2013 CALENDAR

NovemberBig Data & Marketing Innovation SummitNovember 13 & 14Miami

Data Science Leadership Summit November 14 & 15Chicago

Big Data FestNovember 27London

Big Data Innovation SummitNovember 28 & 29Beijing

DecemberBig Data in FinanceSummitDecember 5 & 6New York

OctoberBig Data & Predictive Analytics Summit October 17 & 18Dublin

Big Data InnovationSummitOctober 31 & November 1Mumbai

AprilWomen in Big Data & Tech SummitApril 11 & 12San Francisco

Big Data Innovation SummitApril 11 & 12San Francisco

Hadoop Innovation SummitApril 11 & 12San Francisco

Data Visualization SummitApril 11 & 12San Francisco

Big Data Innovation SummitApril 18 & 19Hong Kong

Big Data Innovation SummitApril 30 & May 1London

JanuaryBig Data Innovation SummitJanuary 30 & 31Las Vegas

FebruaryHadoop InnovationSummitFebruary 20 & 21San Diego

JuneBig Data Innovation Summit June 13 & 14Singapore

Big Data & Analytics for PharmaJune 12 & 13Philadelphia

Big Data Innovation SummitJune 20 & 21Toronto

Big Data & Analytics in Retail June 20 & 21Chicago

MayBig Data & Analytics in Healthcare May 15 & 16Philadelphia

Big Data & Advanced Analytics in Government May 23 & 24Washington, DC

SeptemberBig Data Innovation SummitSeptember 12 & 13Boston

Data Visualization SummitSeptember 12 & 13Boston

Big Data Innovation SummitSeptember 19 & 20Sydney

Partnership Opportunities: Pip Curtis | pcurtis@theiegroup.com | +1415 992 5349 Attendee Invitation: Sean Foreman | sforeman@theiegroup.com | +1415 692 5514

Big Data 2013 CALENDAR

Women

Finance

CXO Healthcare

Expected

Flagship

Government

High Tech Pharma

Hadoop

What you get...• Access to over 200 hours of On-demand training on topics that are important to you, like S&OP, FP&A, Predictive

Analytics , Supply Chain, Strategic Planning, Inventory Optimization, Integrated Business Planning and more• Access to our extensive training library. Whenever your team needs to benchmark or gain some key actionable ideas,

they just watch a quick video.• Monthly newsletters with industry insights and important news - vital for up-to-date info and methodology.

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What is the IE. Network?IE. is the premier forum for Finance, Operations Planning & Business Analytics education. Gain insight and optimize results with un-biased actionable business education available on-demand and delivered by your peers. Stay on the cutting edge of the latest trends within S&OP, FP&A & Business Analytics, all without having to leave your desk.

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