Day 2 – Thursday, March 30, 2017
7:15 AM | Breakfast & Networking
Location: Ballroom Reception |
8:00 AM | Introduction and Logistics
Location: Ballroom |
8:10 AM | Welcome
Location: Ballroom |
8:30 AM | Keynote Speaker – Nate Silver
Location: Ballroom Fireside chat with Nate Speaker: Tracy Kerrins The Signal and the Noise Speaker: Nate Silver |
9:45 AM | Keynote Speaker – Tim Guerry
Location: Ballroom Data Provenance – A Brief History and a Bright Future Reimagining the Data Supply Chain in a Big Data World Speaker: Tim Guerry What’s encouraging is a maturing set of technologies that make utilizing rich data to create client and business value possible: data storage is no longer the obstacle it once was, the number of data sources is exploding, and new tools for analysis, data visualization, data management and robust modeling, are available and evolving. Despite all of this, “getting the data” is still a major impediment for unleashing these powerful insights. Many of our data supply lines are prisoners of the past—they are overly complex and siloed, batch oriented, dependent on disparate technologies, and require manual upkeep. Stronger data management practices which could help, sometimes lead to a “right vs. fast” divergence that further complicates the eco-system. It’s time to rethink and redesign the entire data supply chain using the technology, tools and techniques now at our disposal. |
10:45 AM | AM Break & Expo
Location: Ballroom Reception |
11:00 AM | Break Out Sessions VI
North Carolina Opportunities in the Data Economy Location: Salon 2 Building a ‘Data-Driven Culture’ in your organization Location: Salon 3 Big Data’s Disparate Impact Location: The Great Room II Addressing the sources of this unintentional discrimination will be difficult technically, difficult legally, and difficult politically. In the absence of a demonstrable intent to discriminate, the best legal hope for data mining’s victims would seem to lie in disparate impact doctrine. That hope would largely be in vain. After an overview of American anti-discrimination law, offered through the lens of Title VII’s prohibition of discrimination in employment, it will become possible to understand why the standard approach to discrimination law will be difficult to apply here. These challenges also throw into stark relief the tension between the two major theories underlying anti-discrimination law: anti-classification and anti-subordination. Finding a solution to big data’s disparate impact will require more than best efforts to stamp out prejudice and bias. Rather, it will require new regulatory strategies, some of which may require that we once again reexamine the meanings of “fairness” and “bias.” Data: The Power & Promise of Precision Health Location: Salon 1 How will we accomplish this “precision health?” A significant share of the power and promise of precision health will come from the collecting and assembling data from disparate human and electronic sources (e.g., genetics, family history, environment, lifestyle), analyzing and understanding the data, and then communicating the data analysis in a way that is actionable (as appropriate) for improved health outcomes. This panel addresses the challenges and opportunities for precision health from industry and research perspectives on clinical trials, drug development and safety, bioinformatics, and pharmaceutical data analytics. |
11:45 AM | Lunch & Expo
Location: Ballroom Reception |
12:45 PM | Keynote Speaker – Ric Elias
Segment of One Location: Ballroom |
2:00 PM | Break Out Sessions VII
The Future of Healthcare: Driven by Analytics Location: Salon 1 & 2 Next Generation Analytics Architecture Location: Salon 3 Fraud detection systems in most banks have traditionally been reactive in nature, with suspicious transactions being investigated and analyzed after the fact, offering very little ‘real’ protection from fraud. However, with emerging trends in analytics techniques and data architecture, banks and financial institutions are seeing significant opportunities to modernize their fraud detection and management functions. Predictive modeling are replacing transactional rule based detection engines to score and detect potential fraudulent transactions. Advances in storage architecture is enabling use of full historical data sets instead of samples to greatly improve model accuracy. In addition, banks are looking to incorporate machine learning into fraud detection models to continuously adapt to fast changing environments and behaviors Our presentation will provide an overview of next generation data architecture patterns that overcome the limitations of traditional fraud management systems and enable more proactive, accurate and nimble fraud management functions in banks. |
2:45 PM | Afternoon Break & Expo
Location: Ballroom Reception |
3:15 PM | Break Out Sessions VIII
Payments Industry Analytics Location: Salon 1 Accelerating adoption of Analytics in Financial Services Industry Location: Salon 2 Driving Digitization: A Model for Corporate Analytics Training Location: Salon 3 Artificial Intelligence in the Enterprise Location: The Great Room II Model Risk Management Location: The Den |
4:15 PM | Keynote Speaker – Ritika Gunnar
Transforming with Cloud and Artificial Intelligence Location: Ballroom |
5:15 PM | Expo
Location: Ballroom Reception |