Big Data InnovationBig Data in Sin City

January 22 & 23, 2014Caesars Palace, Las Vegas, NV

Confirmed Speakers

Las Vegas 2014 Speakers

• Sr Director, Data Science, Samsung

• VP, Metrics & Analytics, Macy’s

• Director, Outcome Analytics, UoM

• Sr Director, Game Analytics, Ubisoft

• Chief Data Officer, Baltimore City

• Chief Data Officer, NYSE

• Chief Architect, MapMyFitnes

• Data Engineer, Cleveland Cavaliers

• Sr Researcher, Johnson Research Labs

• Chief Data Officer, Seattle Children’s

• Chief Information Officer, Big Fish Games

• Global Insights & Science, General Mills

• VP, Audience Insights, Tivo

• Director, Real World Data, Pfizer

• Director, Analytics, FDNY

• Head of Data Science, Tapjoy

• Strategic Analytics, Live Nation

• Director, Analytics, Ambit Energy

• Director, Digital Analytics, QVC

• Senior Software Engineer, LinkedIn

• Chief Scientist, ShareThis

• Chief Informatics Officer, UCSF

More speakers & keynotes coming soon...For the latest speaker lineup please click here

The leading summit for Big Data Innovation, The most senior of speakers in the space join to educate, inspire and lead this fascinating technology revolution

Past Delegates include

• Director, Analytics - EA

• Senior Manager, Analytics - Facebook

• Vice President - Google

• Director, Analytics - Coca-Cola

• Director, Analytics Solutions - Disney

• Data Scientist - Twitter

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 analytics industry. You will be meeting senior level execut ives 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. I l lustrated 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

Featured Speaker & Presentation

Dr. Kostman is a Data Scientist, Mathematician and Psychologist. Over the past 15+ years he has provided data-driven insights into human behavior for organizations ranging from the Fortune 500 to the U.S. Federal Government.

He presently leads the Data Science and Strategic Analytics function at Samsung Telecommunications America - where he directs a team of professionals working at the leading-edge of Data Science, Predictive Analytics, and Big Data Mining.

The Leading Edge of Data Science

Recent advances in Big Data Mining, Predictive Analytics, and CyberPsychology are being combined to provide extraordinary insights into the reasons why buyers buy, consumers click, and voters commit.

JT KostmanSenior Director, Data ScienceSamsung

Join us for a glimpse of cutting-edge advances in Data Science with one of the field’s most respected practitioners and forward thinkers, Dr. JT Kostman, as he discusses newly developed methods that transcend traditional data analyses by combining insights from Cognitive Science, Behavioral Economics, and Game Theory – along with advances in Computational Psycholinguistics, Machine Learning, and Bayesian Probability – to allow Data Scientists to cross the Silicon|Carbon Divide and (literally) read minds and influence behaviors, at scale.

Speaker Information

In his current role as Chief Data Officer of NYSE Euronext, Steve Hirsch is responsible for the data vertical which includes data governance, data architecture, database development, operations, platform engineering, storage, and dataflow automation. Prior to entering the exchange space at Archipelago (which later merged with the NYSE), Steve served in other data centric roles at various companies, including Nextcard, one of the first online providers of consumer credit, as well as household names Del Monte Foods and the Walt Disney Company. Steve’s passion for technology began early on in life, coding his first database engine and accounting system while he was still in elementary school and co-founding his first software development firm during his high school years.

Empowering the Data Scientist through Self-Service Data Provisioning

Today, the analytic needs of most organizations are no longer met by the processes and tools of the data warehouse and data mart models of years and decades past.   Data volumes are growing exponentially… data structures are frequently changing… new data sources are being born every day all over the world, and data reservoirs are being filled, that must be tapped.  Organizations need a model to quickly access all of the data assets of a company and provision them to the analytics platform that is best suited for the analysis at hand. 

Steve HirschChief Data OfficerNYSE Euronext

Lenin develops online and social game dev operations and analytics strategy. Design and develop technical and operational strategy, processes, data processing, data warehouse with both traditional and non traditional data sources and technologies.

Big Data - Challenging Journey from Startup to Enterprise

Big Data is neither myth nor a buzz word. It is a challenge. Like RDBMS was 25 - 30 years ago. Lenin Gali will share the challenges he faced and gratification he got from solving them both at a startup and enterprise in this entertaining session.

Lenin GaliSenior Director, Games AnalyticsUbisoft

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 Member Segmentation & Targeting Platform

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 LuuSoftware ArchitectLinkedIn

Speaker Information

Designed text processing pipeline for eDiscovery. This classified, found social network clusters, de-duped, and found near-dupes in 200k documents (mostly email), helping the client prioritize search in a multi-million dollar case. The architecture was simple: Optimized stream processing in Python, parallelized using the multiprocessing module and wrapped up in a shell script. The classification was done using an ensemble of the scikit-lean random forest and the statsmodels L1-regularized logistic regression. The dupes/near-dupes were found using a graph clustering algorithm designed to group documents based on overlapping substrings. The social network clusters were based on importance-weighted edge weights.

High Performance Custom Text Analytics, the Easy Way.

Suppose you were handing a small set of labeled documents and from that needed classify 10 million more.  What if you needed to find duplicates and cluster similar documents?   How about finding (LDA) topics within the documents?   What if I told you a system could be built from scratch, using free open source tools, by two people, in less than 1 month?   Moreover, the documents can be analyzed in a matter of hours on a single machine.   We show how analysis of fairly large collections of documents does not require a large complex solution.

Ian LangmoreAdvisor/Senior ResearcherJohnson Research Labs

Making Unstructured Research Data Useful

Research is useful beyond its one point in time or for one group.  In a large organization, research is done all the time in various functions.  This session will showcase how the use of Big Data technologies to mine unstructured research data.  Specifically:

·  Why research data is unstructured and how it is valuable·  What technologies were necessary to make it useable·   What process and organizational changes were needed to enable this

Wayde FleenerGlobal Consumer Insights, Data ScienceGeneral Mills

Diego Klabjan is a professor at Northwestern University, Department of Industrial Engineering and Management Sciences. He is also Founding Director, Master of Science in Analytics. After obtaining his doctorate from the Milton School of Industrial and Systems Engineering at the Georgia Institute of Technology in 1999, in the same year he joined the University of Illinois at Urbana-Champaign. In 2007 he joined Northwestern University. His research and expertise is focused on analytics with concentration on marketing, sustainability, transportation, healthcare, supply chain management, and retail. Professor Klabjan has led projects with large companies such as FedEx Express, BNSF, General Motors, United Continental, and many others, and he is also assisting numerous start-ups with their analytics needs.

Is the Technology Ready for Big Data Analytics?

Big data solutions are primarily used for storage and querying. While return on investment can be obtained based on these two functionalities, the window of opportunity substantially expands if various analytics-based approaches can be performed directly on big data platforms. There are important differences between traditional approaches and mostly yet-to-be-developed robust solutions for big data analytics. The current state of big data analytics will be summarized,   the important differences discussed, and the challenges ahead shared. 

Diego KlabjanDirector, Master of Science in AnalyticsNorthwestern University

Speaker Information

Healthcare information systems that combine patient reported outcomes with secondary data (EMR, billing, HMO, Medicare, Medicaid, Veteran Administration). Consulting on healthcare informatics, agile development, data quality, business analytics, data warehousing, statistics and outcomes.

Reducing the Dimensionality of Big Data Analytics: Why & How?

There are two potentially conflicting directions in Big Data Analytics - we want to operate with larger data sets  and we want this data to generate more useful information. At the same time larger data sets inevitably   lead to   higher rate of systematic errors (some examples will be shown) that masks the relationships of interest (or even produces false relationships). A priori decomposition of the complex data operation systems in healthcare   as a method of resolving this conflict is proposed (some examples will be shown).

Boris BershadskyDirector, Outcome AnalyticsUniversity of Minnesota

Leads and champions all Macy’s Employee Benefits strategies. Oversees all financial and compliance for Macy’s Health and Welfare plans including budgeting, forecasting and reporting. Responsible for developing dashboards and reports that allow Macy’s to make business intelligent decisions, improve operational efficiencies, and increase shareholder value.

The Secret to Making Magic at Macy’s

Spoiler alert:   It’s our Employees.   Our Employees are the magic makers at Macy’s.   They work hard to surprise and

delight our Customers each and every day.   With over 180,000 employees in over 1,000 locations, Human Capital is at the heart of the magic in America’s Department Store.  It is vital we attract, select, retain, and engage the best people that can create magical moments in our stores.  To do this it takes data – lots of it.Come learn how Macy’s has developed tools to effectively share Human Capital data across our organization swiftly and effectively, allowing stakeholders to make business decisions in a flash.   We will share how we created a successful HR Metrics team and engaging dashboards.   It has not all been easy and sometimes we say it was a “Miracle on 34th street that made it all come together.  But we are excited to share with you our learning lessons, best practices, successes, and the secrets to our success.

Jenna McHughVP, Benefits & HR Metrics & AnalyticsMacy’s

Web Analytics with Business Intelligence – Streamlining Big Data Insights

Web analytics is an area of tremendous value in today’s business environment.   Using packaged solutions businesses are able to gain insights and optimize their websites to maximize conversion, engagement, and customer retention.   While great packages are available, packaged tools limit the ability of analysts to dig deeply into their data and offer maximum insight.

A solution to this challenge developed at Oodle, Inc (acquired by QVC in Jan 2013) will be discussed.  Data was

exported from a variety of sources (log files, web analytics data export, and Mongo DB NoSQL database) into a SQL Server Database.   Data was transformed into a star schema data warehouse following methodology of Kimball and others.   OLAP Cubes were built on top of this star schema to allow for rapid querying, combination of data sources, and deep dives across many dimensions and measures.

An overview of the system and a demonstration of capabilities will be given.   Common challenges to the approach will also be discussed.

Colin ShepherdDirector, Digital AnalyticsQVC

The Information

Silver Pass

$1495Access to all sessions &

networking events

$1295Early Bird Price(before Nov 15)

Diamond Pass

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

membership & Strategic Analysis Report

$1795Early Bird Price(before Nov 15)

Gold Pass

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

membership

$1595Early Bird Price(before Nov 15)

Registration Pricing

Big Data Innovation SummitDate: January 22 & 23, 2014Location: Las VegasVenue: Caesars PalaceRoom Block Booking: Click Here for online booking alternatively call +1 866 227 5944 quoting Innovation Enterprise SummitFurther Venue Info: Click Here

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For larger groups or special requests contact Elliott by calling 415 315 9404 or email ejay@theiegroup.com

* Team discounts are applicable at the point of registration only.

Click or Call...

+1 415 315 9404 +1 323 446 7673 Register Online

Group Discount Offers3 Silver Passes: $3000 ($1000 per attendee)5 Silver Passes: $4750 ($950 per attendee)3 Gold Passes: $4200 ($1400 per attendee)5 Gold Passes: $6250 ($1250 per attendee)3 Diamond Passes: $4800 ($1600 per attendee)5 Diamond Passes: $7250 ($1450 per attendee)

Please note that the Early Bird Pass Rate expires November 15, 2013. Please reserve your pass today to receive the lowest rate available. Early Bird Pass Rates are below the full price on the prices below.

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1. Delegate Information...

2. Pass Types...Early Bird Pass Options until Nov 15, 2013

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

Regular Pass Options after Nov 15, 2013 Silver Pass: $1495 Attendees ____ Gold Pass: $1795 Attendees ____ Diamond Pass: $1995 Attendees ____

Group Discount Pass Options 3 Silver Passes $3300 ($1100 per attendee) 5 Silver Passes $4750 ($950 per attendee) 3 Gold Passes $4200 ($1400 per attendee) 5 Gold Passes $6250 ($1250 per attendee) 3 Diamond Passes $4800 ($1600 per attendee) 5 Diamond Passes $7250 ($1450 per attendee)

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

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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 December 20, 2013 incur an administrative charge of 50%. If you cancel your registration after December 20, 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 SummitJanuary 22 & 23, 2014 | Las Vegas | NevadaFor registration or more information on the program, please call Elliott on +1 (415) 315 9404, or fax this registration form to +1 (323) 446 7673

3. Payment Options...

For larger groups or special requests contact Elliott by calling 415 315 9404 or email ejay@theiegroup.com

Schedule

Networking Drinks 17.00 - 19.00

January 23

Session One 08.30 - 10.00

Coffee Break 10.00 - 10.30

Session Two 10.30 - 12.00

Lunch 12.00 - 13.30

Session Three 13.30 - 15.00

Coffee Break 15.00 - 15.30

Session Four 15.30 - 17.00

Day Two

January 22Day 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

17.00

Session Five 08.30 - 10.00

Coffee Break 10.00 - 10.30

Session Six 10.30 - 12.00

Lunch 12.00 - 13.30

Session Seven 13.30 - 15.00

Coffee Break 15.00 - 15.30

End Of Summit

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For sponsorship information contact Giles at ggb@theiegroup.comF TI L

Confirmed Sponsors Gold Sponsor

Silver Sponsor

Exhibitors

Partnership Opportunities: Giles Godwin-Brown | ggb@theiegroup.com | +1 415 692 5498Attendee Invitation: Sean Foreman | sforeman@theiegroup.com | +1 415 692 5514

NovemberBig Data & Analytics for PharmaNovember 5 & 6, Philadelphia

Big Data & Marketing Innovation SummitNovember 12 & 13, Miami

Data Science Leadership Summit November 12 & 13, Chicago

Big Data FestNovember 27, London

Big Data Innovation SummitNovember 27 & 28, Beijing

DecemberBig Data in Finance SummitDecember 3 & 4, New York

Big Data & Analytics in Banking Summit December 3 & 4, New York

OctoberBig Data & Predictive Analytics Summit October 15 & 16, London

Big Data InnovationSummitOctober 30 & 31, Bangalore

AprilBig Data Innovation SummitApril 9 & 10, Santa Clara

Big Data Infrastructure SummitApril 9 & 10, Santa Clara

Data Visualization SummitApril 9 & 10, Santa Clara

JanuaryBig Data Innovation SummitJanuary 22 & 23, Las Vegas

FebruaryHadoop InnovationSummitFebruary 19 & 20, San Diego

The Digital Oil!eld Innovation SummitFebruary 20 & 21, Buenos Aires

Big Data & Analytics Innovation Summit February 27 & 28, Singapore June

Big Data Innovation Summit June 4 & 5, Toronto

Big Data & Analytics for PharmaJune 11 & 12, Philadelphia

Big Data & Analytics in Retail June 18 & 19, Chicago

MayBig Data Innovation SummitMay 14 & 15, London

Big Data & Analytics in Healthcare May 14 & 15, Philadelphia

Big Data & Advanced Analytics inGovernment May 21 & 22, Washington, DC

Chief Data Of!cer SummitMay 21 & 22, San Francisco

SeptemberData Visualization SummitSeptember 10 & 11, Boston

Big Data & Analytics Innovation SummitSeptember 17 & 18, Sydney

Big Data Innovation SummitSeptember 25 & 26, Boston

Big Data

Women

Finance

CXO Healthcare

Expected

Flagship

Government

High Tech Pharma

Oil & GasHadoop

MarchBig Data Innovation SummitMarch 27 & 28, Hong Kong

2014 Calendar

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

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

Affordable. Cutting Edge. Convenient. Invest in innovative business education that will help you benchmark and validate current and future initiatives that can be leveraged to optimize business results and effective decision making. IE. membership content spans numerous industry sectors and includes presentations from many of the world’s leading companies.

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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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