Day 2 - 14 November 2019

09:30AM

Chris Tomlinson

Director

Data Science Foundation

Associated Talks:

09:30AM - Day 2

View Big Data Business Solutions: Chair’s Welcome and Opening Remarks

09:30AM - Day 1

View Enterprise AI: Chair’s Welcome and Opening Remarks

View Full Info

Big Data Business Solutions: Chair’s Welcome and Opening Remarks

. Chris Tomlinson, Director, Data Science Foundation

09:50AM

Ben Weber

Distinguished Data Scientist

Zynga

Associated Talks:

09:50AM - Day 2

View Automated Feature Engineering at Zynga

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Automated Feature Engineering at Zynga

Zynga is a publisher for mobile gaming with studios located across the globe. We have a diverse portfolio of games and our data scientists need to be able to provide actionable insights across diverse event taxonomies. One of the challenges that we face is that we want to build data products that scale across our catalog of titles, while minimizing the amount of domain knowledge needed in order to build predictive models. An approach we use is automated feature engineering to solve a variety of use cases ranging from anomaly detection to propensity modeling to clustering.This session will discuss how Zynga is leveraging recent machine learning libraries to take data products from prototype to production that scale across all of our titles. We are utilizing Python libraries to translate our data sets from narrow and deep to shallow and wide representations that empowers our data scientists to apply supervised and unsupervised learning methods. We’ll discuss how we’ve scaled up these libraries to work with massive datasets on PySpark using Pandas UDFs, and made feature generation an accessible tool for our analytics organization. The result of this infrastructure is that our data scientists are spending less time on developing models, and instead are focusing on using predictive models to improve our games and live services.We’ll provide a deep dive into our modeling infrastructure and show how we translate our tracking data into a representation that powers segmentation, propensity, and anomaly modeling. Along the way, we’ll call out pitfalls that we encountered, issues we faced when scaling up these methods, and some takeaways that your organization can apply when leveraging automated feature engineering.

. Ben Weber, Distinguished Data Scientist, Zynga

10:20AM

Chris Tomlinson

Director

Data Science Foundation

Associated Talks:

09:30AM - Day 2

View Big Data Business Solutions: Chair’s Welcome and Opening Remarks

09:30AM - Day 1

View Enterprise AI: Chair’s Welcome and Opening Remarks

View Full Info

Mitchell Mason

Senior Offering Manager on the Watson Assistant Service

IBM

Associated Talks:

12:10PM - Day 1

View Lessons learned from applying conversational AI

10:20AM - Day 2

View Keynote Panel: Creating a data-driven culture

10:20AM - Day 1

View Keynote Panel: Driving Digital Transformation through AI & Deep Learning

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Ramesh Menon

Vice President, Product

Infoworks

Associated Talks:

-

View Infoworks.io

10:20AM - Day 2

View Keynote Panel: Creating a data-driven culture

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Jules Malin

Director, Data Science & Analytics

GoPro

Associated Talks:

11:30AM - Day 2

View Case Study: GoPro

10:20AM - Day 2

View Keynote Panel: Creating a data-driven culture

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Meenal Iyer

Director, Enterprise Analytics and Reporting Platforms

Macy's

Associated Talks:

12:00PM - Day 2

View Blueprint for a successful Data Monetization Strategy

10:20AM - Day 2

View Keynote Panel: Creating a data-driven culture

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Keynote Panel: Creating a data-driven culture

  • Establishing evidence-based decision making as a core part of the digital workplace 
  • Defining a clear strategy to leverage data whenever and wherever possible to enhance business efficiency and effectiveness 
  • Putting big data at the heart of your business  
  • Closing the data literacy gap, hiring talent and getting buy in from the top. 

 

Moderator: . Chris Tomlinson, Director, Data Science Foundation
. Mitchell Mason, Senior Offering Manager on the Watson Assistant Service, IBM
. Ramesh Menon, Vice President, Product, Infoworks
. Jules Malin, Director, Data Science & Analytics , GoPro
. Meenal Iyer, Director, Enterprise Analytics and Reporting Platforms, Macy's

11:00AM

Networking Break

11:30AM

Jules Malin

Director, Data Science & Analytics

GoPro

Associated Talks:

11:30AM - Day 2

View Case Study: GoPro

10:20AM - Day 2

View Keynote Panel: Creating a data-driven culture

View Full Info

Case Study: GoPro

GoPro casestudy to follow soon…

. Jules Malin, Director, Data Science & Analytics , GoPro

12:00PM

Meenal Iyer

Director, Enterprise Analytics and Reporting Platforms

Macy's

Associated Talks:

12:00PM - Day 2

View Blueprint for a successful Data Monetization Strategy

10:20AM - Day 2

View Keynote Panel: Creating a data-driven culture

View Full Info

Blueprint for a successful Data Monetization Strategy

Data is a constantly evolving asset, and unlike other assets it may be both appreciating and depreciating simultaneously. A key step towards recognizing the evolving nature of this evolving and ever-changing asset is to realize that the enterprise that generates this asset is also ever-changing and growing.

A successful data monetization strategy requires a well-thought out approach that focuses on the revenue generating and impact generating opportunities that are consistent with an enterprise’s overall strategy.

There are two primary avenues to data monetization. The first focuses on leveraging data to improve a company’s internal operations, productivity, products , end customer interactions and services. The second involves identifying new revenue opportunities (products, markets, customer segments) and/or making data available to customers and partners.

. Meenal Iyer, Director, Enterprise Analytics and Reporting Platforms, Macy's

12:30PM

Tarun Sood

Head of Data and Analytics

Vanguard Institutional Investor Group

Associated Talks:

12:30PM - Day 2

View Telling a story with data and analytics

12:10PM - Day 1

View Keynote Panel: Data analytics for intelligent decision making

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Telling a story with data and analytics

  • What is data storytelling and how is it evolving?  
  • Combining data visualisation and narrative techniques to deliver insights  
  • Going beyond reporting and dashboarding 
. Tarun Sood, Head of Data and Analytics, Vanguard Institutional Investor Group

12:50PM

Networking Break

02:00PM

Bill Schmarzo

CTO, IoT and Analytics

Hitachi Vantara

Associated Talks:

-

View Hitachi Vantara

02:00PM - Day 2

View Afternoon Keynote: Making Big Data the center of your business model

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Afternoon Keynote: Making Big Data the center of your business model

  • What problems is Big Data helping to solve? 
  • What data will be used? How will it be generated and analysed? 
  • How to encourage Big Data Innovation and stay ahead of the pack. 
. Bill Schmarzo, CTO, IoT and Analytics, Hitachi Vantara

02:30PM

Hugh Simpson

Global Solutions Lead - Data & Analytics, A.I. & IoT

Ciklum

Associated Talks:

02:30PM - Day 2

View Finding the unicorns – building a future ready Data Analytics team

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Finding the unicorns – building a future ready Data Analytics team

Building a data & analytics capability can be difficult when there is tight supply of skilled engineers with the commercial aptitude to support a data-driven organisation. Some of the topics we will discuss will be:

  • Agile mindset and customer-centric analytics
  • Technical vs domain experience
  • Outsource vs insource
  • Growing the team
. Hugh Simpson, Global Solutions Lead - Data & Analytics, A.I. & IoT, Ciklum

03:00PM

Calvin Anderson

Head of Commercial, USA

OYO Group

Associated Talks:

03:00PM - Day 2

View Big Data for the Visual Learner

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Big Data for the Visual Learner

The key to growth in a world of technological hyper-evolution is a culture that efficiently executes more insights faster.  And while nothing unveils a prudent next step like rich unbiased data, such clarity rarely exists as “big data” is often fatiguing and multi-dimensional.  This challenge escalates further as algorithms enter the picture and begin to execute as black boxes to all but their creators.  To cope, Sr decision makers often employ teams of analysts to roll up trends not realizing that in order to summarize millions of lines of raw data, a series of decisions must be made before leadership is even at the table.  This vulnerability can lead to enormous effort and expense wasted on redirecting already working arms of the business or resolving issues that don’t actually exist. Thanks to advances in data visualization, many of these errors can be avoided with a base understanding of one’s own raw data combined with an appetite to see the fuller picture.

In this session, through the lens of the lodging business, we will review the core elements of raw transaction data which will provide a base understanding of the data-structures that commonly apply to most industries.  We will explore some of the misconceptions derived from summing and averaging trends too quickly and will discover hidden insights found only when data is revealed as a complete picture.  At its conclusion, attendees will carry away both a cultural and technical data-foundation that will allow them to ask better questions and derive deeper insights from their own businesses.

. Calvin Anderson, Head of Commercial, USA , OYO Group

03:30PM

Samuel Chang

Corporate Vice President

LG Electronics

Associated Talks:

-

View LG ThinQ

03:30PM - Day 2

View Panel: Data and the customer

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Mark Burnette

Vice President, Digital Insights Solutions

Hitachi Vantara

Associated Talks:

-

View Hitachi Vantara

03:30PM - Day 2

View Panel: Data and the customer

View Full Info

Frost Li

Growth Advisor

Formerly from Wish

Associated Talks:

03:30PM - Day 2

View Panel: Data and the customer

View Full Info

Dr. Li Gao

Technical Lead

Lyft

Associated Talks:

03:30PM - Day 2

View Panel: Data and the customer

View Full Info

Panel: Data and the customer

  • What problems is Big Data helping to solve? 
  • What data will be used? How will it be generated and analysed? 
  • How to encourage Big Data Innovation and stay ahead of the pack.
. Samuel Chang, Corporate Vice President, LG Electronics
. Mark Burnette, Vice President, Digital Insights Solutions, Hitachi Vantara
. Frost Li, Growth Advisor, Formerly from Wish
. Dr. Li Gao, Technical Lead, Lyft

04:10PM

Session Close

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