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
-
8:30 pm

Networking Dinner

8:30 pm
-
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

Welcome Address and Opening Remarks

9:10 am
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9:55 am

Keynote Presentation

Overcoming the Data/Privacy Divide

To drive greater focus and flexibility in business capability, enterprises of all types are investing heavily in customer data capture and customer data analytics capabilities, whether from traditional loyalty programs, online data capture, or in-store/on-premise mobile tracking. As more and more personable data is collected or created however, the specter of customer privacy issues begin to loom larger and larger. Enterprises need to take a long hard look at the information they are capturing and the manner in which it is being used to determine whether the potential value outweighs the potential risk, and whether the incentive offer to the customer is sufficient to overcome any reticence on their part.

Takeaways:

  • Data privacy is not a show-stopper; customers are willing to share personal information if the payoff is sufficiently worthwhile
  • Not all information gathering needs to be personal and in many cases anonymous aggregated data can be just as instructive, certainly about trends
  • Where information gathering does get personal, opt-in with balancing opt-back-out requirements are essential

10:05 am
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10:35 am

Executive Exchange

Thought Leadership


Sponsored by:

View detailsCIGNEX Datamatics, Inc.CIGNEX Datamatics, Inc.

10:40 am
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11:10 am

Executive Exchange

Think Tank

Big Data and Analytics at the Scale of Mobility

The explosive growth of data volume and data variety that have characterized this new Big Data era are set to head in a steeper upward trajectory as enterprises collectively begin to exploit the massive data flows that are coming out of mobile devices. As the volume of mobile devices eclipses that of human beings on the planet, just imagine the data volume that can be captured when every device and every individual is streaming a constant set of contextual “status” information. Data growth by itself however is only a small portion of the story, as to have value this data must be analyzed in essentially real-time in order to create actionable outcomes.

Takeaways:

  • Big Data today may be big, but every single one of the “v’s” that compose it (Volume, Variety, Velocity, Veracity and Value) is set to increase exponentially as a result of wholesale mobility adoption
  • The ability to analyze, interpret, and find meaning in this vast sea of data will be single biggest differentiator in enterprise success
  • Enterprises will have to walk a fine line when it comes to privacy of the information they collect to ensure the continued ability to do so

Presented by:

Scott Sokoloff, Chief Data Officer, OrderUp

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

Sponsored by:

View detailsSAPSAP

12:10 pm
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12:40 pm

Executive Exchange

Think Tank

Big Data & Healthcare Analytics – Bringing Clinical Data into the Business of Healthcare

Everyone is in the same boat; we’ve collectively spent the last few years implementing and fine tuning various EHR, Hospital Information, and other clinical systems and have amassed a wealth of data that could be used for so much more than it’s current limited application. In a world where healthcare is moving away from a fee for service model, we need to find ways to aggregate this information and use it to build patient care programs that improve care quality and patient outcomes, while lowering costs and performing well in a risk contract. Breaking data silos and building an holistic single pane of glass view into our clinical data, we can begin to identify our risk populations, design programs of efficient care management teams, and make use of long term proactive health planning for better care AND better costs.

Takeaways:

  • Understand that the key to efficient and effective risk-based payment models is deep data analytics
  • See how the data needed to make such models work exists in our information systems, but is siloed
  • Discuss best practice strategies to break down these silos and drive cost and care improvements

Presented by:

JT Kostman, Chief Data Scientist , Keurig Green Mountain, Inc.

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


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 Tools, Data Governance, and Information Governance

Presented by:

Richard Kessler, Executive Director, Head of Group Information Governance , UBS

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

Aggregating Diverse Data Types

Low-power, low-complexity computing devices are set to invade the enterprise and indeed have begun to do so already in a number of cases. As these devices proliferate, so will the data that they generate and, at least initially, so will the proprietary data formats that they use. Until comprehensive standards can be developed, implemented, and enforced, enterprises will be left to deal with hodge-podge data that needs to be cleanly aggregated before it can be analyzed and until analysis can occur, that data is just meaningless noise. Enterprising CIOs will recognize this challenge early and works closely with both IoT sensor providers as well as business unit leaders to ensure that appropriate investments are made, and that processes are put in place so that value can be extracted from the data that is being gathered.

Takeaways:

  • New endpoints mean new data feeds in potentially almost endless new structures and new formats
  • The volume of data creating sensors that will invade the enterprise means the volume of data to be aggregated will be beyond anything seen before, as will the variety of types, and the speed with which aggregation is needed
  • A comprehensive data model is essential to success

Presented by:

View detailsStacey Jones, Data Architect, UPS

Think Tank

Data Integration in an Open Healthcare World

One of the potential side benefits to emerge from the switch to Accountable Care is the increasing pressure that is being exerted on everyone in the industry to become more open with healthcare data. The value however could go far beyond incremental improvements. Payers will become a cornerstone of this new world because they have the most robust data collection and aggregation processes, their only limitation being their inability to collect enough of the right data from providers and patients. By moving to a model where all data from a healthcare transaction, from EMR data all the way to claims payment data, a more consistent and holistic view can be generated, and deeper insights discovered. Payer CIOs need to begin laying the groundwork for this future today by looking at their data collection and analysis platforms, their communications capabilities, and their interoperability standards to ensure the technology doesn’t impede the progress.

Takeaways:

  • Big Data initiatives have had tremendous benefit in every industry to which they have been applied; next up is healthcare
  • In healthcare, Payers will need to take the lead given their data management capabilities but will need to partner tightly with providers and patients to collect the requisite data
  • Payer IT departments need to begin preparing for this change now, thinking about the impact on their data architecture and data sharing processes

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 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

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

6:00 pm
-
7:00 pm

Cocktail Reception

7:00 pm
-
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
-
8:50 am

Networking Breakfast

9:00 am
-
9:45 am

Keynote Presentation

Clinical Data Analysis is Healthcare’s Big Data Challenge

The payment reform introduced by the Accountable Care Act is having significant ripples across the industry not the least of which is putting healthcare organizations in the position to reduce procedures and spending while simultaneously increasing overall health and patient outcomes. Leading edge organizations are realizing that they can achieve these seemingly opposite goals by more accurately and granularly understanding their patient community, the health issues they are suffering, and the causes of those issues. By defining the patient population into discrete subpopulations healthcare organizations are more able to leverage appropriate care at appropriate times but defining those subpopulations is a challenge for which big data analytics is the key.

Takeaways:

  • Healthcare organizations are under increasing pressure to do more with less and so need to find new solutions to old problems
  • At the same time the potential for visibility has never been higher given the volume of data being collected as a result of widespread EHR adoption
  • CIOs must leverage big data technologies to help their organizations understand the patient community to improve health and lower cost

9:55 am
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10:25 am

Executive Exchange

Thought Leadership

Augment your Analytics Ecosystem Through Scalable Graph Analytics

Enterprises have made major investments in analytics over the years, and these investments are largely paying off. Today however, data is exploding - new sources, more volume, more complexity. Business leaders suspect there is hidden value in this data but today's approaches often constrain their ability to find and exploit this value. The power of discovery should not be constrained. Analysts should be free to act on a hunch, uninhibited by rigid data structures and traditional approaches.

10:30 am
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11:00 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

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 mush 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:

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

11:05 am
-
11:20 am

Networking Break

11:25 am
-
11:55 am

Executive Exchange

Think Tank

Big Data and Analytics at the Next Level

The explosive growth of data volume and data variety that have characterized this new big data era are set to head in a steeper upward trajectory as IoT moves from being a fringe technology, to a mainstream capability. When a single Boeing 787 is able to capture 70Tb of data per flight from thousands of individual sensors throughout the vehicle, just imagine the data volume that can be captured when not just every plane, or even every vehicle, but every device and every individual is streaming a constant set of “status” information. Data growth by itself however is only a small portion of the story, as to have value this data must be analyzed in essentially real-time in order to create actionable outcomes.

Takeaways:

  • Big Data today may be big, but every single one of the “v’s” that compose it (Volume, Variety, Velocity, Veracity and Value) is set to increase exponentially as a result of IoT
  • The ability to analyze, interpret, and find meaning in this vast sea of data will be single biggest differentiator in enterprise success
  • Enterprises will have to walk a fine line when it comes to privacy of the information they collect to ensure the continued ability to do so

Presented by:

View detailsJoe DeCosmo, Chief Analytics Officer, Enova InternationalEnova International

Think Tank

Big Data Analytics the Key to Smart Grid Value

Smart Grid technology is nothing new but the penetration rates continue to lag in many areas of the country, as overall installation of smart meters themselves is less than 25% nationally in large part due to low cost electricity in many areas. Smart Grid is about far more than cost management however and delivers benefits in four key areas: Increased customer satisfaction, improved overall utility reliability, enhanced operational efficiency, and improved safety and risk mitigation. To be able to properly leverage these benefits however, Utilities must understand what is happening across the smart grid by capturing the wealth of data and properly analyzing it through the use of data analytics. Join our panelists as they discuss the broad benefits of smart grid adoption, the benefit of big data analytics in smart grid deployments, and the pitfalls to be avoided in both deployments.

Takeaways:

  • Smart grid allows a wealth of benefits that can increase revenues, reduce cost, and create value
  • These improvements are realized by exploiting patterns in the data that is captured by smart meters and other smart grid devices
  • The complexity, variability and sheer quantity of the information being gathered means specialized Big Data solutions are needed to realize the value

Presented by:

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

12:00 pm
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1:00 pm

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

Panelists:

Scott Sokoloff, Chief Data Officer, OrderUp

Paul Childerhose, Director, Data Governance- Traded Products , Scotiabank

1:00 pm
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1:10 pm

Thank You Address and Closing Remarks

1:10 pm
-
2:10 pm

Grab and Go Luncheon