Bright Lights, Big City Data

The way that governments view the vast stores of data they collect and maintain is changing. Through open data and transparency programs, governments are opening up their data sets to outside developers, civic activists, academics and journalists – creating new opportunities for application development, research and policy analysis.

This collaboration with outside data consumers is creating unique and unexpected uses of government data, allowing for an unprecedented view into how governments are performing and creating new ways of analyzing social policies.

This “open data movement” is also changing the way that government’s themselves think about their data. It is helping to break down the traditionally siloed and parochial view among government departments about how data is used. Government managers are now looking across the enterprise (and across governments) for opportunities to collaborate with each other, and are starting to think strategically about their data and how it is used to inform policy decisions.

In the next several years, the pace at which governments open their data will accelerate and government managers will come to view the role of “data steward” as one of the most critical functions of public sector entities.

Biography

Mark Headd is a writer, speaker, teacher and thought leader on communication technologies and open government. Self taught in programming, he has been developing telephone, mobile, speech recognition and messaging applications for almost 10 years. In August, 2012, the Nutter Administration selected Mark to become the city’s first Chief Data Officer, to lead Mayor Nutter’s open data and government transparency initiatives. Mark previously worked as Director of Government Relations at Code for America, culminating a period of almost 2 years of collaboration with the organization on open government and civic hacking projects in across the country and in Philadelphia.

Mark has worked for technology companies from the Delaware Valley to Silicon Valley. He previously served in government, working for three years as the chief policy and budget advisor for the State of Delaware’s Department of Technology and Information. He has also served as Director of the Delaware Government Information Center, as Technology Adviser to former Delaware Governor Thomas R. Carper, and in the New York State Senate as a budget and finance analyst. For the last several years, Mark has been active in the OpenAccessPhilly initiative which is focused on encouraging citizen engagement, digital inclusion and technology-driven innovation in Philadelphia. He has been active in the support and promotion of the OpenDataPhilly.org data portal, and helped in organizing the recent OpenData Race.

Mark has built open government software applications for the District of Columbia, the Sunlight Foundation, the New York State Senate, and the cities of New York, San Francisco, Toronto, Baltimore and Philadelphia. He is an organizer and participant in civic hacking events across the country, including Philadelphia and Baltimore. He holds a Master’s degree in Public Administration from the Maxwell School of Citizenship and Public Affairs at Syracuse University, and is a former adjunct instructor at the University of Delaware teaching a course in electronic government.

Big Data Do’s and Don’ts

An integrative summary of big data do’s and don’ts based on the presentations at the Big Data Conference.

Biography

Paul A. Pavlou is Professor of Management Information Systems, Marketing, and Strategic Management and a Stauffer Senior Research Fellow at the Fox School of Business at Temple University. He received his Ph.D. from the University of Southern California in 2004. His research focuses on e-commerce strategy, digital business strategy, and the development of research methods.

His research has appeared in top academic journs and his work has been cited over 2,000 times by the Social Science Citation Index (SSCI) of the Institute of Scientific Information (ISI) and over 7,500 times by Google Scholar. Paul was ranked first in the world in publications in the two top IS journals (MISQ and ISR) in 2011 and second in 2010.

Paul is a Senior Editor at JAIS. He is also currently a guest Senior Editor of a Special Issue of MISQ on “Digital Business Strategy.” Earlier he served as a guest Senior Editor of a Special Issue of MISQ titled “Novel Perspectives of Trust in Information Systems” that was published in June of 2010, and also as a guest Senior Editor of a Special Issue of JMIS on ‘Trust in Online Environments’ published in 2008. He is currently working on several big data and analytics projects.

Know Thy Customer: Next-Generation Techniques for Turning Big Customer Data Into Action

Companies leading the charge in competing with analytics, make data-driven decisions part of their daily practice. But they need to discover, interpret, and respond to key data patterns quickly and intelligently.  Identifying key (and potentially non-obvious) relationships and trends allow the business to rapidly respond to changes in their customers’ needs and behaviors. Come to this session to see how some great companies are creating a core competency around big data analytics with a blend of machine learning technology, cloud computing, and business process under the economic constraints of smaller headcounts and limited budgets. We will explore the next-generation techniques and technologies that today our business leaders are using to create data-driven product strategy and customer-level insight from petabytes of data. Get ideas of how to apply iterative, self-optimizing data analysis in your organization and enable your own analytics center of innovation.

Biography

Ryan Caplan is Founder and CEO of ColdLight Solutions, a Software as a Service technology company who uses next generation automated machine learning technology (called Neuron™) to help businesses make smarter, quicker decisions. ColdLight’s clients include leaders in pharmaceuticals, financial services, media/entertainment and insurance. A pioneer in the software industry, Ryan led an international team of software engineers to develop one of the world’s first real time internet banking platforms. He has also brought consultative leadership to some of the world’s largest companies including Oppenheimer Funds, Rohm & Haas, Aramark, Wyeth, Shire, Comcast, MBNA and Lincoln Financial. Ryan is a frequent guest lecturer on the topics of Advanced Analytics and Entrepreneurship at Fortune 100 businesses and major universities.

Driving Business Performance Through Analytics

Following Wawa’s SAP implementation, the company centralized more data in a corporate data warehouse. Wawa used this data to create a test-and-learn mindset and implemented a data intensive new product test methodology. With this new methodology, Wawa has more accurate analytics to drive quicker fact-based decision making.

Biography

Brian McCaffrey is Wawa’s Director, SAP and Business Process. As part of his role, he leads Wawa’s Business Intelligence team and partners with Finance to drive Wawa’s Enterprise Information Management (EIM) strategy. In August 2011, Garner Group published a case study chronicling Wawa’s EIM journey titled “How Wawa Turned a BI Data Consistency Project Into an EIM Strategy”. Prior to joining Wawa Brian worked for Accenture as a systems integration and IT consultant concentrating in the Retail sector with a specialty in Supply Chain/ Logistics processes and systems. Brian is a Certified Business Process Professional (CBPP) by The Association of Business Process Management Professionals (ABPMP) as well as a certified Process Master by Hammer & Company. He received his Bachelors of Science Business Administration degree from Villanova University and his Masters of Business Administration from The Kenan-Flagler Business School at The University of North Carolina, Chapel Hill.  

Big Data Analytics at Work in Healthcare

The rapidly evolving field of medicine generates petabytes of data across disparate resources from medical claims to patient sample data. Leveraging all available data sources to improve the quality and efficiency of healthcare is paramount to controlling costs of medical care in the United States. Greenplum has been working with leaders in the field, spanning the life sciences, medical providers and prescription drug companies and distributers, to deepen the collective understanding of the healthcare system. In this session, we will review the models and insight in the healthcare system by examining the solutions and conclusions from our predictive case studies.

Biography

Sarah Aerni has a background in the field of Bioinformatics, developing tools to help biomedical researchers understand their data. She received a Ph.D. in Biomedical Informatics from Stanford University in 2012. During her time at Stanford she developed methods incorporating machine learning and other techniques to model the cells in 3-D images of a model organism and analyze human genetic sequences. She also co-founded a start-up providing informatics services to researchers and small companies.

Josh Raysman

Leveraging Big Data for a Healthier World

Big Data @ Pfizer – Understand the implications of the data deluge for the world’s largest bio-pharmaceutical company. Learn about the drivers behind the data growth, the potential it may hold for our ability to improve health & well-being at every stage of life, and what Pfizer is doing today to maximize current & future possibilities.

Biography

Josh Raysman is an accomplished business leader with over 15 years of experience in the field of Information Management (IM) & Business Intelligence (BI).

Currently, Mr. Raysman serves as a Senior Director, for the Global Data Management function within the world’s largest pharmaceutical firm, Pfizer, Inc. In his role, Josh is responsible for leading an organization that delivers complex business intelligence solutions across the enterprise as well as the design, implementation and management of all underlying technology platforms.

Josh has established a track-record of successful Information Management Strategy Development, and BI/IM Project Delivery within Pfizer as well as external organizations. He has spoken on multiple BI/IM-related topics at a variety of industry conferences.

Prior to joining Pfizer, Josh was a Senior Principal with an industry-leading IM consultancy, where he served as a leader within the group’s Health and Life Science practice. He has also been a Certified Instructor and Curriculum Developer for the Business Intelligence and Data Warehousing Certificate Program at the University of California, Berkeley. Josh holds a Bachelor of Arts degree from Emory University.

Caron Kogan

The Process of Predicting with Big Data

Increasing accuracy realized with predictive analytics is one of the opportunities offered by the use of Big Data. Past applications have sought this goal through the use of forecasting and modeling techniques based upon sample sets of data. The difference afforded by using new techniques for mining intelligences from Big Data, is that we are no longer constrained to samples because of limitations on processing time and/or capacity. Today’s emerging and new technologies for big data analytics provide the ability to leverage entire sets of massive and complex data to significantly enhance the accuracy of predictive modeling.

To reap this value, requires discipline, planning, and processes. Predictive Analytics is both an art and a science but without a structured approach to its outcome, an organization will not realize its full potential.

This session provides an overview of proven guidelines for building effective predictive analytics against the richness to be found in the volume, velocity and variety of Big Data.

Biography

Caron B. Kogan is the Strategic Planning Director for Big Data within IS&GS of Lockheed Martin (LM) and is responsible for leading the strategy and implementation of IS&GS’s Big Data initiatives and investments.

Ms. Kogan has more than 20 years executive management experience in computer, communications and financial industries with national and international firms. She has led business strategy, product development, information technology (IT), customer care, field operations and engineering for start-up and high-growth companies. Having managed programs that developed and implemented solutions for Business Intelligence, CRM and Enterprise Applications, she brings experience from both, the perspective of a customer, and that of a vendor.

Prior to joining Lockheed Martin, Ms. Kogan held various executive roles – as VP Engineering & Operations for an affiliate marketing company in San Diego, VP-Information Management for Mission Federal Credit Union and CIO for a start-up offering a web conferencing solution. At NCR, she led program and product management teams in the development of MPP systems for large scale data warehouse solutions and drove architectural strategy for their worldwide Services organization.

Ms. Kogan holds a Bachelor’s of Engineering and Masters of Management Science from Stevens Institute of Technology.

David Jonker

Re-inventing Business Processes with Real-time Insights

Big Data insights can revolutionize the way you do business when you can apply them continuously in business operations. Companies like Mitsui Knowledge Industries are re-inventing entire processes by leveraging in-memory technology innovations to analyze data in real-time. Using specific examples, this session explores how companies can achieve the impossible when massive data sets are married with real-time analytics.

Biography

David Jonker is director of Big Data at SAP, and is responsible for the go-to-market initiatives across SAP’s data management and analytics platforms.

Previously, David Jonker lead product marketing teams for Sybase’s data management & analytics product lines offering solutions for Big Data, data warehousing, cloud, mobility, and embedded systems. David’s career also includes more than 14 years in software engineering and product management roles.

David has a degree in Systems Design engineering from the University of Waterloo.

Clark J. Frogley

Insurance Fraud Analytics – The Data You Cannot Afford To Ignore

Over 160 countries, more than 100 languages, millions of policy holders and hundreds of millions of claims applications constitute the typical data set that AIG deals with on an annual basis. Today, most of that data is reviewed and managed by human beings attempting to provide quick and customer focused response to individuals, small businesses and large corporations in what is often very emotional and difficult situations. Earthquakes, hurricanes, floods, riots, political turmoil, fires and theft all result in someone needing help from their insurance carrier. However, within that data, industry experts and benchmarks indicate somewhere between 1 and 2% of paid losses are fraudulent. Put another way, between 3 and 10% of annual claims submissions are identified as suspicious and require investigation.

Managing data in a vertical environment creates a situation that relies on happenstance and luck to identify much of the potentially suspicious documentation that is the lifeblood of an insurance company. Data analytics, and specifically predictive analytics and link analysis, allows real time three dimensional analysis to determine that 3 policies under different names all come back to the same cell phone number; one person was the witness to 3 automobile accidents in a given month; or a large group of injured workers are all going to the same medical doctor, receiving the same diagnosis, and are represented by the same attorney no matter where they live in the state. For a company like AIG, that means hundreds of millions of dollars are at risk due to potential insurance fraud. Data analytics is being used to lead the way to working more globally, more intelligently and much more efficiently in detecting potential fraud in the insurance business.

Biography

Mr. Frogley is responsible for the global strategic development and operational management of the fraud investigative function within Chartis. He has direct responsibility for the investigations and investigative personnel across 160 countries where Chartis does business, focusing on suspicious claims, premium, underwriting and provider fraud.

Prior to joining Chartis in January 2009, Mr. Frogley held the position of Managing Director, Global Head, Fraud Prevention and Investigations, Deutsche Bank, AG. Prior to that, Mr. Frogley held various senior positions within Deutsche Bank and Goldman Sachs to include Managing Director of Corporate Security and Business Continuity for all of Asia and North and South America, and Regional Head of Global Sourcing and Contracts in Asia Pacific. Mr. Frogley also held several senior positions within the FBI to include Assistant Legal Attaché – U.S. Embassy, Tokyo, Japan where he was a diplomatic member of the embassy’s Transnational Crime, Counter Intelligence and Security Teams.

Mr. Frogley is well known for his expertise in Anti-Money Laundering, Anti-Fraud, Business Transformation, Mergers and Acquisitions Due Diligence, Change Management, Corporate Security, Business Continuity, and Operations over the last 25 years and has been a featured speaker at numerous conferences in the US and Asia Pacific.

Mr. Frogley speaks fluent Japanese and holds a Bachelor of Arts in Asian Studies and Japanese from Brigham Young University, and an MBA Summa Cum Laude from Temple University’s Fox School of Business.

Ravi Chawla

From Attaining to Sustaining Membership – Using Big Data and Predictive Analytics in Marketing

Attaining and sustaining customers is a widespread business objective for every company. Business metrics do a great job summarizing the past. But if you want to predict how customers will respond in the future, there is one place to turn — predictive analytics. The analytics team within IBC’s Informatics division has worked with Marketing Services on models to help them achieve this objective. A predictive model was built to predict small group attrition so that we can target those customers proactively. Another model that was worked on was a response model to predict the likelihood that individuals on purchased prospect lists will enroll in an individual product.

Biography

Ravi Chawla, MS, MBA is Director of Advanced Analytics in the Informatics department at Independence Blue Cross. Ravi’s experience in the healthcare industry includes ten years at Independence Blue Cross, where his primary focus has been on medical cost and utilization analysis, member analytics and risk stratification. In the last couple of years, his areas of responsibility have expanded to include program evaluation, outcome research and predictive modeling. He has also worked for three years at the Health Alliance Plan in Detroit, Michigan where his area of responsibility included provider performance reporting and physician incentive programs.

Ravi has an M.B.A from Wayne State University in Detroit, Michigan and more recently completed his Executive Leadership Program at AHIP.