Day 2: Monday August 5th, 2019
9:05 am - 9:10 am Chairperson's Remarks
9:10 am - 9:40 am Re-evaluating Risk Assessment And Expanding The Breadth Of Alternative Data Sources
The Fintech Revolution has already begun to transform the ways in which financial institutions and multinational corporation’s access and leverage risk throughout a diverse set of business units. Explore the ways in which the availability of real-time, streaming data can allow you to gain a 360-degree view of the role credit decisions play in both the lives of your customers and business model. As fintech continues to its path of disruption it’s increasingly important to be aware of how to approach issues that might arise between front and back office teams regarding the role analytics will play in the middle to long term. (i.e.- real time accounts management, open banking as a means to serve previously underservedpopulations, etc.)
Significant themes discussed include:
- Potential regulatory challenges which could affect growth opportunities
- How can companies leverage fintech to encourage better financial habits for particularly among tech-savvy Millennial consumers?
- Developing models to factor bias and encourage ethics in AI
- Successful use cases of chatbot technology and importance of deploying at appropriate points of the customer journey
- Using data enrichment to provide contextual awareness
Andrew ReiskindSenior Vice President, Data Strategy
9:40 am - 10:10 am Welcome to the Analytics Economy
Breakthroughs in connectivity and compute power are giving us the power to collaborate and solve problems we never could before. As analytics evolve from a force that helps organizations to a force that drives them, we are seeing the dawn of an Analytics Economy. In this economy, data is the natural resource, insights are the currency, and there’s a fundamental change in how value is created. In this presentation, we’ll discuss how to unlock the potential of this new economy, with an emphasis on artificial intelligence and the Internet of Things. We’ll also examine the need for a unifying platform that makes analytics accessible to everyone, everywhere – and explain how such a platform can turn a world of data into a world of intelligence.
10:10 am - 10:40 am Data Innovation in the Face of Policy Updates, GDPR, CCPA, ITP & Other Fun Intialisms
Data Innovation is the lifeblood of most companies in the media & ad-tech space, as they strive to build personalized, customized experiences and features for consumers, while trying to connect consumers with the most relevant and monetizable advertisements. Over time, organizations undergo shifts in their data policy, reacting not only to external events and competitive challenges, but also due to changes in risk appetite. Recently, regulations such as GDPR, CCPA - not to mention several additional states considering creating consumer data privacy laws - have further exacerbated these challenges. ITP is yet another development that portends to limit innovating with data.
In this talk, I will cover the journey Verizon Media has undergone since Verizon closed the acquisition of Yahoo. I will provide a peek into select data solutions, and discuss how we are building consumer oriented constructs and capabilities in response to the changing policy and regulatory landscape.
Varun BhagwanVice President, Product & Engineering- Data, Measurements, & Insights
11:25 am - 11:55 am Business Meeting
11:55 am - 12:25 pm Business Meeting
12:25 pm - 12:55 pm Business Meeting
1:05 pm - 2:05 pm Avoiding Extinction Through Strategic Backsourcing and Digital Transformation
This session will focus on the evolution of diversified digital transformation sourcing models that help elevate organizations from underperforming to best in class.
Dr. Laz MederosSenior Director, Business Intelligence & Analytics
2:45 pm - 3:45 pm Practitioner Roundtable Discussions
Earlier in the Exchange, we collected your insights and challenges in the data and analytic space using the Thoughtexchange social learning tool. During this follow-up session, you’ll have dedicated time to sit with your peers and develop an action plan to improve data and analytics operations.
3:45 pm - 4:15 pm Adopting AI / ML and Avoiding Pitfalls Along the Way
Why are enterprises in every industry adopting Artificial Intelligence (AI) and Machine Learning (ML)? Is it really all about killer robots and mobile phone assistants? What does AI / ML really mean for your organization? What does it take to build and develop AI-based solutions to drive competitive advantage?
Topics discussed will include:
- Criteria for success with AI / ML
- Building and developing AI / ML solutions
- Avoiding common mistakes and pitfalls
Victor GhadbanField Chief Technology Officer
Brainweave4:15 pm - 5:00 pm Strategies for Tackling Defensive and Offensive Data Management
How are data leaders applying best practices to managing the data supply chain, empowering stakeholders to collaborate, and sharing trusted data throughout the organization? Discuss how the industry is successfully automating data lineage and governance, creating transparency to build trust and accessibility, reducing 100’s of hours of time to find and deliver data down to minutes – all while staying compliant.
In this BrainWeave Session you’ll discuss how to:
- Trust and deliver data across multiple BI platforms
- Manage the wake of data redundancy left behind from data prep tools
- Assure data privacy in the modern BI environments
- Effectively buy and use 3rd party data
- Collaborate, rank, and recommend data
- Harmonize multiple compliance regulations on the same data
Sue HabasVP- Strategic Technologies
Masterclass4:15 pm - 5:00 pm Achieving the "Nirvana" of Self-Service Data Science
Many analyst professionals might think it’s some kind of “data nirvana” to achieve self-service data science. It’s easy to see why. You have a difficult time hiring the right talent. Based on the Annual CDO Survey from Gartner, 59% of Chief Data Officers say they feel too far behind on attracting and hiring analyst talent. Once you do hire talent, organizations report they can only analyze 12% of their data accurately.
The great news is that it's possible to achieve this “data nirvana” and offer self-service data science. Dr. Mike Kim, Co-Founder and CTO of Outlier, will present in this session the following:
● What are some of the current challenges to consider before migrating to self-service?
● How automating collection and analysis phases of data science can help to achieve self-service
● Examples of organizations who have adopted a self-service data science philosophy
Dr. Mike KimCTO and Co-Founder
5:15 pm - 5:45 pm Business Meetings
5:45 pm - 6:15 pm Business Meeting
6:15 pm - 6:45 pm Business Meeitngs
6:45 pm - 7:15 pm Developing an Agile, Collaborative Data Science Team & Creating Enterprise-Wide Data Literacy
American Tire Distributors, founded in 1954, has enjoyed explosive growth during the past decade thanks to a renewed focus on leveraging the power of data analytics to meet the evolving needs of wholesalers. Creating and institutionalizing a data science team is fraught with many challenges and requires significant organizational alignment and collaboration. Tim Eisenmann, Chief Analytics Officer & SVP Advanced Analytics, will lead this discussion focused on how to optimize your data science team and scale it up to create significant enterprise value.
Join this session to learn about topics including:
• Effective strategies to operationalize use cases and implement final production while optimizing your data science team
• Aligning the analytics ecosystem to best serve the specific needs of your data science team
• Developing training tools to upskill/reskill end-users to improve last-mile adoption
• Strategies to develop data literacy across the organization and encourage cross-functionality of your data science team
Tim EisenmannChief Analytics Officer
American Tire Distributors
7:15 pm - 8:00 pm Deriving Value From IoT Data with Analytics At Scale
Analyzing Internet of Things data has broad applications in a variety of industries, from smart cities to smart farms, from predictive maintenance on costly medical machines to asset tracking and usage-based insurance. These IoT use cases clearly have wildly different requirements, yet if you drill down into the architectural choices made at each individual company, you see something surprising: The production architectures show a remarkable number of similarities. Every industry using IoT needs to manage and analyze sensor, time-series, and other large volume data sources. Because of the unique demands of IoT, widely varied use cases end up with very similar technology and architectural needs. Join us for an interactive discussion to share and discuss your architectural plans for deriving value from the high volumes of sensor data from the Internet of Things in ultimately reducing
costs, improving customer satisfaction, or even generating entirely new business models.
Jeff HealyDirector, Product Marketing
7:15 pm - 8:00 pm Harnessing the Power of Real Time Data Analytics
The proliferation of connected devices and improved connection speeds has allowed the emergence of real-time analytical capabilities. Enterprise-wide adoption of robust real-time analytics allows end users to incorporate more agility into their decision making process.
• Real-time feedback for DevOps pipeline
• Challenges related to building an architecture able to handle the spikes and volatility of real-time data
• Keeping sight of offline analytics capabilities requirements and building a data architecture that can reconcile online and offline computing needs.
7:15 pm - 8:00 pm The Next Frontier
Explore opportunities to build on the analysis we already do (using new data or gaining additional insights from existing data) and identify actions we can take beginning tomorrow.
Michael RobertsDirector of Customer Engagement