PDF Download May 17-19, 2015 Agenda (PDF)

Big Data Summit
May 17-19, 2015

↓ Agenda Key

View detailsKeynote Presentation

Visionary speaker presents to entire audience on key issues, challenges and business opportunities

View detailsExecutive Visions

Panel moderated by Master of Ceremonies and headed by four executives discussing critical business topics

View detailsThought Leadership

Solution provider-led session giving high-level overview of opportunities

View detailsThink Tank

End user-led session in boardroom style, focusing on best practices

View detailsRoundtable

Interactive session led by a moderator, focused on industry issue

View detailsExecutive Exchange

Pre-determined, one-on-one interaction revolving around solutions of interest

View detailsFocus Group

Discussion of business drivers within a particular industry area

View detailsAnalyst Q&A Session

Moderator-led coverage of the latest industry research

View detailsVendor Showcase

Several brief, pointed overviews of the newest solutions and services

View detailsCase Study

Overview of recent project successes and failures

View detailsOpen Forum Luncheon

Informal discussions on pre-determined topics

View detailsNetworking Session

Unique activities at once relaxing, enjoyable and productive

Sunday, May 17, 2015 - Big Data Summit

2:00 pm
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4:30 pm

Registration and Greeting

4:30 pm
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6:00 pm

6:00 pm
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7:00 pm

Welcome Reception

7:00 pm
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8:30 pm

Networking Dinner

8:30 pm
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10:00 pm

After Dinner Networking

Monday, May 18, 2015 - Big Data Summit

8:00 am
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8:50 am

Networking Breakfast

9:00 am
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9:10 am

9:10 am
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9:55 am

Keynote Presentation

Big data trends, correlation techniques and machine learning

Large banks harnessing big data platform, correlation techniques, machine learning to influence change, automate complex business processes, build as you go integration strategy and harmonize data.

Presented by:

View detailsPrem Tadipatri, Director, Technical Fellow, Risk Finance Integration Strategy, Credit SuisseCredit Suisse

10:05 am
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10:35 am

Executive Exchange

Thought Leadership

Combining Small & Big Data Analytics for Effective Real-Time Actionable Insights from Social Media Sentiment Analysis

With the explosion of social media and proliferation of mobile devices, the importance of social media sentiment analysis is well appreciated. Given the volume of this unstructured data, obtaining real-time insights/action is challenging. A hybrid data-lake architecture which uses Hadoop as well as MongoDB has been very effectively used for such a combined small & big data analytics (The small data real time insights are derived from the batch-mode big data analysis). A building block approach is presented where multiple configurable re-usable “bricks” have been created for NLP based sentiment analysis, personality insights and the hybrid data lake. This “platform” allows to quickly create varying flavours of social media sentiment analysis solutions catering to unique use cases. Ex. a social media engagement solution which evaluates the sentiment around brand keywords and “key influencers” responsible for that. Using personality insights on them, it also allows the enterprise to effectively engage with them on social media.

Sponsored by:

View detailsCIGNEX Datamatics, Inc.CIGNEX Datamatics, Inc.

10:40 am
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11:10 am

Executive Exchange

Think Tank

Building Data Science: Lessons Learned from Transitioning Companies to Data Driven Methodologies

Scott Sokoloff, Chief Data Officer at OrderUp, shares his experiences and insights in how to create a data driven culture. Told through a lens of use cases and personal insights; Sokoloff, engages with the audience to tailor this keynote to the specific questions of those in attendance.

 Having aided numerous companies in their transition to become data driven, Sokoloff knows that there’s no cookie cutter solution but rather the specific circumstances and needs of each enterprise must be taken into consideration. Audience involvement is encouraged and everyone is asked to bring any use case or practical concerns they may have in transitioning their company towards a data driven culture.  

Takeaways:

•             Know Your Business Objectives

•             Invest in Internal Resources

•             Build the Infrastructure for Success

Presented by:

View detailsScott Sokoloff, Chief Data Officer, OrderUpOrderUp

Think Tank

Semantic Standards Enable Financial Data Synergy

Financial services companies want to develop new data analytics products and services for their clients. The increasing complexity and cost of global regulatory compliance diverts attention and resources from those efforts. The development of data standards, through industry partnerships like the Enterprise Data Management (EDM) Council, when combined with semantic technologies creates a synergy that can address both requirements. 

Takeaways: 

  • Development of the Legal Entity Identifier (LEI) from a regulatory mandate 
  • How public/private collaboration can work to the benefit of both 
  • Emerging standards: Financial Industry Business Ontology (FIBO) is an emerging standard from the Object Management Group (OMG) that benefits multiple constituencies 
  • Exploiting semantics to describe data so that it can be used for both data analytics and risk management 
  • Utilizing semantic data standards to create transparency both internally and externally to enhance data governance

Presented by:

View detailsDavid Saul, Senior Vice President & Chief Scientist, State Street CorporationState Street Corporation

11:15 am
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11:30 am

Networking Break

11:35 am
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12:05 pm

Executive Exchange

Thought Leadership

Simplifying the Delivery of Real-Time Business Insight

Using Big Data is a must to create value, improve performance, and to uncover real-time insights for innovation. However, many organizations struggle with managing and leveraging Big Data, seeing it as a series of challenges to overcome rather than an opportunity. In this session, we will discuss how the majority of enterprise Big Data issues are cost-effectively solvable with an in-memory computing platform. We’ll show you how large organizations like John Deere are leveraging a platform that combines the power of in-memory and analytics, to completely transform their business. Learn how you can simplify your ability to access data from a variety of sources, process large volumes of data rapidly, and deliver business results in real-time, while lowering IT costs.

Sponsored by:

View detailsSAPSAP

12:10 pm
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12:40 pm

Executive Exchange

Think Tank

Big Data and Real-Time Analytics to Improve the Customer Experience

At Enova International, a global online financial services provider, providing an easy and fast customer experience is mission-critical. As more and more data becomes available about consumers, the opportunity to leverage that data in real-time during a customer interaction creates opportunities to improve products, streamline processes, and automate decision-making, while also improving customer service and satisfaction. Through real-life use cases and examples, Joe will demonstrate how to drive ROI with your big data and analytics initiatives. 

Takeaways: 

  • Understand how social, geographic, and transactional data can add value to your business;
  •  Identify creative uses of data analytics in the call center; 
  • How to balance privacy and business value to ensure a sustainable business model.

Presented by:

View detailsJoe DeCosmo, Chief Analytics Officer, Enova InternationalEnova International

Think Tank

Privacy and Data Protection Issues to Consider Before Starting Big Data Projects

Given the myriad of business reasons for embarking on Big Data projects, the privacy and data protection issues associated with a Big Data project may not be top of mind, but they should be. Unexpected privacy and data protection issues can derail any Big Data project, and focusing on these issues at the outset is easier and less expensive than managing them in a crisis situation later on. 

Takeaways: 

  • Discussion of some of the key privacy and data protection issues in 
  • Big Data projects Recommended solutions for dealing with these issues 
  • Predictions regarding future issues and concerns

Presented by:

View detailsLynn Goldstein, Chief Data Officer , New York University- Center for Science and ProgressNew York University- Center for Science and Progress

12:45 pm
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1:15 pm

Executive Exchange

Thought Leadership

A Blue Print to Leverage Next-gen Data Processing Technologies and Trends to Create a Modern Agile Enterprise

Enterprise IT Technologists, Leaders and Business Sponsors are contending with a number of simultaneous trends and forces converging together. Some of these are open-source Big Data platforms like Hadoop and NoSQL, machine learning, the rise of in-memory computing, leverage of low-cost hardware, and real-time streaming analytics. 

This talk aimed at Senior IT Executives will provide an overview of how these forces can be leveraged to create an Enterprise Data Architecture Blue Print. The approach can help create a Modern Agile Enterprise that serves its customers in real-time or near-real-time in a context-sensitive manner, enabled by a powerful blend of both offline and real-time Analytics.

Sponsored by:

View detailsImpetusImpetus

1:20 pm
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2:20 pm

Networking Luncheon

2:25 pm
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2:55 pm

Executive Exchange

Think Tank

The Relationship Between Big Data, Data Governance and Information Governance

The lack of consistency of how Big Data, Data Governance and Information Governance are defined, interpreted and aligned is an ongoing source of confusion, especially for those of us that have roles that span multiple domains. During this session, we’ll look at various interpretations of these concepts, review what distinguishes them, consider how they’ve been implemented, and explore what’s possible if they joined up as part of an integrated, enterprise strategy. We’ll then provide practical advice that can be used to improve decision-making, risk management and compliance at your organization all while supporting continuous innovation.

Takeaways:

  • Understand the various perspectives, definitions, interpretations and implementations of key concepts;
  • Explore the characteristics of a holistic, data-focused operating model and all-encompassing strategy; and
  • Learn practical ways to demolish silos, accelerate the change lifecycle, and improve how data-associated investments are targeted.

Presented by:

View detailsRichard Kessler, Executive Director, Head of Group Information Governance , UBSUBS

Think Tank

Big Data, Big Success

As the retail market space becomes increasingly crowded and competitive, retailers need to put themselves in a position to differentiate themselves from their competitors, either by pricing or by offering. In order to be able to do this, retailers need to put themselves in a position where they have a deeper and broader understanding of not just the needs and wants of their customers, but also their motivators and triggers. IT Leaders realize that they need to invest in powerful analytics programs that allow them to leverage the wealth of client data they are capturing, find the relevant patterns and insights, and use those to aggressively attack the market and establish dominance.

Takeaways:

  • Successful retailers have long used data analytics to ensure a competitive edge relative to their peers
  • Data is becoming more ubiquitous and the sources by which it is derived are growing exponentially
  • Personalization of experience is a strong indicator of relationship success, but can only be achieved by truly understanding the client through data analytics

Presented by:

View detailsDonnie Yancey, Chief Operating Officer, MapquestMapquest

3:00 pm
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3:30 pm

Executive Exchange

Thought Leadership

Making Big Data Actionable

There is a lot of hype and misinformation about big data in the marketplace. Many companies are confused about how to get started, what actions to take, and what pitfalls to avoid. Additionally, focus is shifting from simply capturing and discovering new insights with big data to operationalizing those insights. The industrial revolution took manufacturing processes from an artisanal practice to a modern technological marvel that is able to manufacture quality items at massive scale. The same type of revolution must happen with analytics and big data. Based on the new book The Analytics Revolution, this talk will address technological, organizational, and cultural points that must be considered to succeed in making big data actionable and operational and will aim to provide attendees a solid direction to take their big data analytics initiatives.

Sponsored by:

View detailsTeradataTeradata

3:35 pm
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3:50 pm

Networking Break

3:55 pm
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4:25 pm

Executive Exchange

Think Tank

Big Data as Part of Your Data Strategy

New data technologies are evolving at an unprecedented pace. The traditional RDBMS is no longer the only choice for storing your data. Big data technologies such as Hadoop and other data technologies such as Data Virtualization, NoSQL, In-memory databases, Columnar Databases, and Graph databases offer new capabilities, but hold the potential to simply distract or disrupt business. Do relational databases still play a role? Using the wrong technology for the problem at hand can be expensive, time consuming, and counter-productive. I will discuss the importance of developing a data strategy for your company and how to determine the correct technologies. 

Takeaways: 

  • Understand your data consumption needs 
  • Document your data ecosystem 
  • Develop your data strategy to apply the best data technology

Presented by:

View detailsStacey Jones, Data Architect, UPSUPS

Think Tank

The Role of Data Lake in Building Agile Big Data Analytics

The healthcare industry is known for slow adoption of technology specifically when it comes to Data and Analytics. While we still need to solve the identified use cases, modern data architectures help us to dream big, start small and scale fast to build efficient data platforms. This presentation is about solving data analysis challenges in healthcare from non-traditional databases like Cache and MUMPS through Data Lakes. A Data Lake is not a silver bullet to solve all the problems but provide a data virtualization platform to build a business driven analytics through rapid experimentation and gradually integrate with schema on read platforms. This presentation talks about how we can build modern data architectures, Data Lakes, with technologies like Storm, Kafka and schema-on-read with H-catalogs. This presentation also talks about who can adopt Data Lakes with modern big data technologies irrespective of their industry. 

Takeaways: 

  • Challenges with unconventional data sources 
  • Efficient ways to dump the data for rapid experimentation and build quality business data 
  • Do we need schemas in the modern data architectures? 
  • Who can adopt Data Lakes? 
  • Where do they fail?

Presented by:

View detailsRama Kattunga, Systems Director - Enterprise Analytics, Presence HealthPresence Health

4:30 pm
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5:30 pm

CIO Executive Visions Panel

Using Data & Analytics to Drive Business Transformation

Big Data initiatives have become a reality among almost every company today, however, what we have seen is lots of initiatives have become just science projects and did not deliver on early expectations. This situation needs to be reversed quickly because those organizations that are being successful with Big Data and analytics programs are rapidly leaving those that are unsuccessful in their wake. Big Data and analytics has the potential to be transformational for the enterprise, but IT leaders need to be making the right investments, in the right areas, to ensure optimal success. This panel discussion will focus on how to use data and analytics to drive true business success and show some real examples of companies and individuals who made a difference.

Takeaways:

  • Analytics is not a new capability and has always been aligned with the most successful companies
  • The roles of IT and the lines of business are changing when it comes to data and analytics programs
  • The business benefits of analytics programs can be huge but efforts need to be constrained so that they don’t turn into flights of fancy, yet set free enough that they find the “unknown unknowns” that truly drive transformation

Moderated by:

View detailsJames Quin, Senior Director of Content and C-Suite Communities, CDM MediaCDM Media

Panelists:

View detailsScott Hallworth, SVP, Enterprise Data & Chief Model Risk Officer, Capital OneCapital One

View detailsJoe DeCosmo, Chief Analytics Officer, Enova InternationalEnova International

View detailsChaarles Fogelgren, Global Head - Laboratory Data Management, QuintilesQuintiles

View detailsBarclay Blair, Founder & Executive Director, Information Governance InitiativeInformation Governance Initiative

View detailsKenneth Viciana, VP, Enterprise Data Strategy, EquifaxEquifax

6:00 pm
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7:00 pm

Cocktail Reception

7:00 pm
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8:30 pm

Executive Networking Dinner

8:30 pm
-
10:00 pm

After Dinner Networking

Tuesday, May 19, 2015 - Big Data Summit

8:00 am
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8:50 am

Networking Breakfast

9:00 am
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10:00 am

CIO Executive Visions Panel

Defining Data Governance

Data volume, data variety, and data velocity have all grown exponentially over the last few years, the so-called Big Data explosion. And while this increased organizational focus on data, the information it contains, and the insights that can be gleaned from it promises tremendous opportunity, that opportunity isnt achieved without overcoming significant challenges. Whether it be the increased need for better data quality (an issue unresolved from the small data days), more efficient and effective data management, answering questions around data ownership vs. stewardship, or even increased regulatory pressure as a result of data security and data privacy, this increased focus on data has created an increased need for Data Governance. Join our panelists as we discuss the thorny issue of Data Governance: what it is, how it works, why you need it, and who should be responsible for it.

Takeaways:

  • Data management issues have existed as long as data has existed but the Big Data boom has increased these challenges exponentially 
  • Resolving data management issues requires a strong data governance program to make rules, resolve issues, and enforce compliance 
  • Determining what to about data governance is the easy part, determining how and by whom it should be done will be the real challenge facing IT

Moderated by:

View detailsBarclay Blair, Founder & Executive Director, Information Governance InitiativeInformation Governance Initiative

Panelists:

View detailsScott Sokoloff, Chief Data Officer, OrderUpOrderUp

View detailsPaul Childerhose, Director, Data Governance- Traded Products , ScotiabankScotiabank

View detailsHolly Starling, Director, Information Governance, AutoTrader.comAutoTrader.com

Yogesh Joshi, Head of Big Data and Analytics, AIG

Ranjana Young, Senior Vice President, Enterprise Data , Northern Trust Corporation

10:10 am
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10:40 am

Executive Exchange

Think Tank

Big Data Analytics - A Fundamental Shift

We have moved from an information-poor to an information-rich society. Practically unlimited availability of data, computing, networking, and socio-mobile connectivity are fundamentally altering our world. In particular, they are enabling businesses to become more effective and efficient by using big data analytics - collecting all relevant data and automating their processing to drive decision-making. This represents a fundamental shift from traditional business analytics where limited amount of structured data is batch-processed to produce standard Business Intelligence reports. We will assess the current state of big data analytics, technology and business trends, and their enormous implications to the future of all businesses. 

Takeaways:

  • How Big Data analytics is different from traditional business analytics
  • What businesses are getting out of big data analytics
  • How Big Data analytics will become critical to every business
  • How you should enter into Big Data analytics or do more of it

Presented by:

View detailsScott Hallworth, SVP, Enterprise Data & Chief Model Risk Officer, Capital OneCapital One

10:45 am
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11:00 am

Networking Break

11:05 am
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11:35 am

Executive Exchange

Think Tank

Data Integration at the Scale of Mobile

As enterprises grow in scale and complexity, the amount of data and data types they collect increases and the introduction of mobile data (either mobile collected or mobile consumed) just accelerates this pace. As data volumes and varieties grow, enterprises are increasingly challenged to efficiently and effectively manage the integration of this disparate material, particularly when the pressure to do so quickly and accurately is becoming more significant. Mobility really is making a world where data integration is becoming an overwhelming problem and if IT leaders do not find a way to address it, their business peers will be left to face the consequences.

Takeaways:

  • Context is essential; without a good understanding of what data and data needs exist, there will be no possibility of efficient and effective data integration
  • The further away the source of the data (and it doesn’t get much further than mobile data) the less it can be trusted so mobile data needs extra scrutiny
  • To effectively integrate data you must first integrate master data and governance rules as these will define the ground rules for all data integration

Presented by:

Yogesh Joshi, Head of Big Data and Analytics, AIG

11:40 am
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12:10 pm

Executive Exchange

Think Tank

Leveraging Big Data to Improve Government Efficiency

Governments allocate a large share of resources in the United States Economy. Lacking a profit motive, the incentives moving government to adopt efficient and effective business practices are different. We can mimic such pressures using budgets, oversight, performance management, and audits. However the end result, regardless of the motive, is to make decisions that alter our inputs, production processes, and outputs of the many goods and services made available by cities, counties, school districts, universities, and states. We will discuss the data resources my governments possess and how we go about leveraging these data assets to build a case for change. Unlike more private businesses, we make most of these decisions in full view of the public - we will discuss the potential risks and rewards to such a model. Finally, as big data impacts people, business and government, we will discuss implications for future regulations.

Takeaways:

  • Governments can leverage big data to increase efficiency, lowering the costs or improving the quality of public goods and services.
  • Translating data into insights and a persuasive case for change can be a challenge, but one with some opportunities. 
  • The regulation of big data is still in infancy, as these data assets change our life and economy, government will set the rules.

Presented by:

View detailsDavid Stringfellow, Chief Economist, State of UtahState of Utah

12:15 pm
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12:25 pm

12:30 pm
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1:30 pm

Grab and Go Luncheon