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Friday, January 29th, 2016

Day 3

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7:15 AM Networking Breakfast

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Advisory Board Meeting (By Invitation)

8:15 AM Chairperson's Opening Remarks

8:20 AM Scaling and Reusable Analytics: A Deep Dive Conversation

David Dunne , Senior Managing Director, IB Transformation, & Chief Data Officer, TIAA-CREF

This session will talk about the critical factors and elements to scalable analytics, reusable data sets and multiple domain uses.  If you are faced with analytics challenges from multiple domains such as operations, financial and marketing - this session is for you. We will explore approaches and key components to allow analysis and scientists to focus without the worry of finding and understanding your data.  

David Dunne
Senior Managing Director, IB Transformation, & Chief Data Officer
TIAA-CREF

9:00 AM Challenges and Opportunities with Big Data and Open Source Technologies

Swapnil (Neil) Jadhav , Chief Data Officer/Head of Business Intelligence & Analytics, City of Carlsbad

Chief Data Officers are tasked with determining how best to capitalize on an organization’s data to improve decision-making for business outcomes, fine-tune marketing programs, respond to changes in customer demand, and seize upon new business opportunities. The biggest challenge is that the new technologies — and new levels of data volume, variety and velocity — require an experimental approach. It's a learning exercise and time and resources are precious.

Many of the best and best known big data tools available are open source projects, but with the growing number of open source projects and supplementing vendors in this field, it is difficult to build an accurate strategy to leverage the right set of tools to drive analytics. This session will help narrow down the best-in-class open source tools and help you build or refine your big data strategy to kick start your projects with very little investment. The highlights of this session are:

  • What are the current trends in open source big data technology?
  • What are the top 10 open source big data technologies that can speed up your implementation?
  • What are the challenges you are having in dealing/implementing open source?
  • A quick 1 page strategy to implement in your organization
  • Case studies and success stories of open source big data implementation
  • Moving beyond barriers and challenges to successful outcomes

Swapnil (Neil) Jadhav
Swapnil (Neil) Jadhav
Chief Data Officer/Head of Business Intelligence & Analytics
City of Carlsbad

9:40 AM Managing the Shift from Big Data Analytics to Data Products

Ari Caroline , Chief Analytics Officer, Memorial Sloan Kettering Cancer Center

"One-off" data science models can be helpful in answering "one-off" questions. However, in most large organizations, the same questions can be repeated over and over, only with varying inputs and parameters. In these circumstances, data science models that are focused on a single expression of a problem are inefficient. Under these circumstances, one-off models should be replaced by robust, flexible data products that allow the end user to ask many different permutations of a similar inquiry. At Memorial Sloan Kettering (MSK), one of these products recently released across all MSK sites is a tool for intuitively searching clinical trials using natural language and for matching patients to these trials using similarity algorithms.

Topics discussed will include:
 
  • When is a data product appropriate?
  • What does a data product team look like?
  • How does a data product team interact with other parts of the organization?

Ari Caroline
Ari Caroline
Chief Analytics Officer
Memorial Sloan Kettering Cancer Center

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10:25 AM Business Meetings

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Networking Break

10:55 AM Business Meetings

11:30 AM Data, Deep Learning, and Distributed Software: actually changing the world with Google

Miles Ward , Global Head of Solutions, Google Cloud Platform, Google

By combining substantial innovations in efficiently storing and processing data, the Cambrian explosion of innovation around machine learning, neural networks, deep learning, convolution and specific artificial intelligence, together with a steep drop in the level of effort required to build automatically scaling globally distributed applications, I think we can all agree we're at a pretty interesting place in time. This "perfect triangle" of accelerating factors is making whole classes of previously unassailable problems suddenly tractable, and in some cases pedestrian.
Miles Ward
Miles Ward
Global Head of Solutions, Google Cloud Platform
Google

Sponsored by: Google Cloud Platform

Google Cloud Platform

12:30 PM End of Exchange