DATAx Digital Data & Analytics Conference 2020 August
August 11 - 13, 2020

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3
Days
2
Tracks
350+
Attendees
40+
Speakers

DATAx Virtual

AUGUST 11, 12 & 13

3 DAYS | 2 TRACKS | UNLIMITED INSIGHTS

DATAx Virtual is a cross-industry event for business leaders, strategists, and practitioners looking for best practices and strategic insights to help increase business growth and gain marketplace advantage.

DATAx Virtual provides a unique blend of data-focused content tailored to help you find real-world solutions to common challenges.

Our program is specifically curated to examine the most relevant topics on the minds of data scientists and business decision-makers. With an emphasis on collaboration, DATAx Virtual is the event where the technical and strategic conversations that change business models are started.

Team discounts are available :
3-4 People: 30% off
5+ people: 50% off

Email enquiry@argyleforum.com  for details.

2020 DATAx Virtual SPEAKERS

What to Expect at DATAx Virtual

Conference Topics

Strategy and Leadership, Artificial Intelligence, Machine Learning, Deep Learning, Structured and Unstructured Data, Data-Driven Culture, Data Governance, Computer Vision, Data Visualization, Natural Language Processing, Data Personalization, Neural Networks, Cryptographic Algorithms, Blockchain, IoT, Customer, and Marketing Analytics, Robotics

Interested in speaking? Please submit your completed abstract to Tina Nacrelli at tnacrelli@argyleforum.com

Audience Details

Our audience will be 400+ business leaders, strategists, and practitioners looking for insights, collaboration, and solutions on how to utilize data to make informed business decisions.

Insights

Bring back actionable insight by participating in three days of candid talks and round tables.

Collaborate with peers in the interactive DATAx Labs. Choose from a series of workshops to fit your business needs and personal goals.

Collaboration

Connect with 400+ data leaders across all industries and experience levels to expand your network.

Meet the disruptive startups and innovators who are changing the world.

Solutions

Discover cutting-edge tools and techniques.

Immerse yourself in automation, data, and mobile technologies that will unleash your potential.

2 Tracks To Choose From

TRACK 1 – Data Science Strategy & Leadership in the Age of Data Dominance

TRACK 2 – Insights & Applications: Using Data to Power Success

Agenda

 

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10:55 AM - 11 AM ET

Opening Remarks

11 AM - 11:45 AM ET

PANEL: The Future of Data

In our inaugural session for the DATAX conference, we introduce key themes to be explored over the course of the event. How will the industry evolve as a result of the increasing amounts of data available to companies? How will AI and machine learning transform the ways in which data scientists do their jobs and grow in their careers? How will leadership evolve to adapt to the IT revolution in data science? Tune in to hear key insights from industry leaders about the rapidly changing data science world, including their predictions for the industry’s future.

Moderator:

Trish Uhl, PMP, CPLPFounderOwl's Ledge LLC

Panelists:

Sherin MathewsSenior Data ScientistMcAfee

Dr. Nels LindahlDirector, Clinical Decision SystemsCVS Health

Tracey Smith President Numerical Insights LLC

11:50 AM - 12:20 PM ET

Data Science Strategy & Leadership - (Track 1)

PANEL DISCUSSION: Structuring Data Teams to Maximize Impact

A strong data team affords you the ability to effectively solve for business problems and leverage the rich resources within data to influence your company’s direction for the future. Lean in on this discuss with Data Science leaders as they share their struggles and successes in organizing data science teams.

In this session, topics of discussion will include:

  • How to best organize data teams within an organization
  • The key to hiring and retaining top-notch  talent
  • Team fluency around financial and  business metrics

Moderator:

Joe FleischerEditorial Director, Finance ChannelArgyle Group

Panelists:

Meghan AnzelcHead of Data & Analytics Spencer Stuart

Charles Mueller, Ph.D.Data Scientist Rackspace Technology

11:50 AM - 12:20 PM ET

Insights & Applications - (Track 2)

PANEL DISCUSSION: Self Service Enablement – Empowering Data Discoveries Across the Organization 

Achieving the level of a data driven organization opens up a new world of possibilities for your organization. With a stable data governance strategy in place and a workforce fluent in data you are able to empower your workforce to drive data focused initiatives across the organization.  

In this session, topics of discussion will include:

  • Defining your data governance strategy
  • Establishing a level of data fluency within your organization 
  • Training on the tools and techniques required to effectively analyze data

Moderator:

Stephen SkinnerVisual Data ArchitectDataBilder

Panelists:

Jordan MorrowGlobal Head of Data LiteracyQlik

Gaja NagarajanHead of Information TechnologyeHealth, Inc.

12:25 PM - 1:10 PM ET

Data Science Strategy & Leadership - (Track 1)

FIRESIDE CHAT: Using Data and AI Intelligent Workflows Across the Talent Spectrum

 To help overcome the broadening skills gap that threatens to undermine the organizations’ digital transformation efforts, talent professionals are leveraging AI, Data, and intelligent workflows. These technologies make it possible to attract, retain and continuously up-skill and re-skill employees to run a successful data-centric business.

In this session, topics of discussion will include:

  • Leveraging AI to attract diverse candidates from a large pool, intelligent job matching
  • Understanding the skills you have, via AI based skills Inference
  • Communicating the skills you need in the future, transparent communication and nudging
  • Closing the skills gap, via AI based personalization
  • Transforming culture and building a skilled workforce adept in digital skills

Vinod UniyalChief Technology Officer (CTO) - Talent DevelopmentIBM Talent & Transformation, Global Services

Trish Uhl, PMP, CPLPFounderOwl's Ledge LLC

12:25 PM - 1:10 PM ET

Insights & Applications - (Track 2)

USE CASE: Developing Data Science to Add Value

The goal of every data science team is to make a significant impact on the business. Teams work hard building some amazing and extremely useful tools that never see the light of day and their potential impact never realized. Join us as we uncover how to organize the development process to keep engagement high and demonstrate added value along the way.

In this session, topics of discussion will include:

  • Obstacles faced by data scientists their data projects
  • How to restructure development, get accurate feedback and demonstrate value
  • How to keep stakeholders involved during project journey. From exploration to implementation

Morgan CundiffData ScientistShopRunner

1:10 PM - 1:25 PM ET

Afternoon Break

1:25 PM - 1:55 PM ET

Data Science Strategy & Leadership - (Track 1)

USE CASE: Business Strategies to Burst the Bias Bubble 

Collaborative decision making under uncertainty happens daily in business. Machine learning obscures bias behind the complexity of its algorithms. Bias is corrosive because it hides in metrics and systems we use to make decisions every day. It gives us false confidence that our decisions are data driven when in reality, they are bias driven.

Even data scientists often don’t understand the data and models well enough to prevent biased outcomes. Autonomous cars are 5% more likely to hit PoC because their training data wasn’t diverse enough. Amazon abandoned their automated candidate screening system because it was biased against protected classes. Join us as we dive into what you can do to control bias within your organization

In this session, topics of discussion will include:

  • Creating a culture that strives to reduce bias 
  • Using Machine Learning systems to reduce uncertainty
  • Reducing uncertainty around key decisions by controlling bias

Vin VashishtaData Scientist, Strategist, AuthorV2 Machine Learning Consulting

1:25 PM - 1:55 PM ET

Insights & Applications - (Track 2)

THOUGHT LEADERSHIP: How CDOs Can Lead the People, Process, and Technology Of Data Defense

  • Why data defense is just as important as data offense to creating analytical models
  •         How do you enable self-service to make structured and unstructured data discoverable and usable for data modelers
  •         How Boomi can accelerate your data defense and turn analytic results into action

Pragnya Paramita Marketing DirectorDell Boomi

2 PM - 2:30 PM ET

Data Science Strategy & Leadership - (Track 1)

How to Effectively Accelerate ROI on Your AI Investments

Every organization wants to use data as its core advantage, but struggle with scaling and accelerating their data initiatives. Many of the challenges can be attributed to the fact that the data, and its applications are advancing faster than the technologies used to process and design them. Join us as we dive into the root cause of many common data challenges and incorporate applied patterns to solve them.

In this session, topics of discussion will include:

  • How to design efficient data models that will enhance the performance of your AI/ML tools
  • How to successfully use applied patterns to address the root cause of your data challenges
  • Real-World solutions to scale and accelerate AI/ML processes

Ronak ShahHead of Data EngineeringCoursera

2 PM - 2:30 PM ET

Insights & Applications - (Track 2)

Augment, Don’t Automate: Drawing Insights from Customer Feedback Using Natural Language Processing 

Companies are frequently faced with large amounts of unstructured text data, like forum comments or product reviews. Important trends can emerge in these datasets, but it can be time-consuming to read through comments, and keyword matching frequently misses critical nuances. We’ll discuss how we’ve approached this problem at Google using Natural Language Processing, with examples of the approach applied to open datasets. We’ll explore how this fits into the ML project lifecycle, with examples of common pitfalls. Finally, we’ll highlight how to use this technology as part of a “human in the loop” approach to supercharge your existing team members.

Peter GrabowskiSoftware Engineering ManagerGoogle

2:30 PM - 2:45 PM ET

Afternoon Break

2:45 PM - 3:15 PM ET

Data Science Strategy & Leadership - (Track 1)

USE CASE: Getting Your Data House in Order – Critical Issues in Advancing Data Governance 

Data is the asset of the present – and the future. Whether it’s generating insights, driving innovative product development or improving decision making, the need for and dependence on big data has never been greater. 

Data is a critical strategic asset for any company looking to leverage the power of AI, machine learning, and other advanced analytics. However, for companies that were not “data-first,” implementing a data governance program that both maximizes the quality of their data and addresses the obligations created by the changing regulatory landscape remains a challenge. This session will explore the critical legal and practical issues a business must consider as it develops and implement compliant and effective data programs.

In this session, topics of discussion will include:

  • How to structure a data governance program that addresses their current regulatory obligations to comply with new privacy and security obligations
  • Best practices in creating a data-focused business culture
  • Real-world examples of trends, challenges, opportunities and developments to come in data collection and use

Jessica B. LeePartner, Co-Chair, Privacy, Security & Data InnovationsLoeb & Loeb

2:45 PM - 3:15 PM ET

Insights & Applications - (Track 2)

FIRESIDE CHAT: How to Maximize Your Training Dollars with Predictive and Performative Analysis

Companies spend tens of billions of dollars on employee training each year, but nearly half of that budget is wasted because employees are not retaining information or incorporating new skills into their jobs. How can companies get more out of their training programs?

Join Tiffany Jarvis, Department Lead for Learning Analytics at Edward Jones, in an engaging conversation with Trish Uhl, Founder of Owl’s Ledge LLC, to learn how companies can use data to systematically assess how employees process new information, allowing them to adjust programs to make sure that the right people are equipped with the right tools.

In this session, topics of discussion will include:

  • A description of new data tools that help companies measure retention of information imparted in training sessions.
  • The use of predictive instruments to help companies assess which employees are likely to benefit from training.
  • How to use “people data” to ensure that training resources are utilized with maximum efficiency.

 

Tiffany JarvisDepartment Leader - Learning AnalyticsEdward Jones

Trish Uhl, PMP, CPLPFounderOwl's Ledge LLC

3:20 PM - 4:05 PM ET

KEYNOTE ADDRESS: How Data is Influencing Change

The pace of change in the world is breathtaking and leading this change is data. How are you charting a path to ensure that data and technology works for us rather than against us? Data Scientists have the power to effect major changes, but first they must adopt new approaches. Join us to learn first-hand how to use data to influence change.

DJ PatilFormer Chief Data OfficerUnited States Office of Science & Technology Policy
& Head of Technology, Devoted Health

4:05 PM - 4:25 PM ET

Q & A with DJ Patil

DJ PatilFormer Chief Data OfficerUnited States Office of Science & Technology Policy
& Head of Technology, Devoted Health

4:25 PM - 4:30 PM ET

Closing Remarks
 

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10:55 AM - 11 AM ET

Opening Remarks

11 AM - 11:45 AM ET

Panel: Seven Deadly Data Sins & Data Virtues

Join us for a provocative discussion about the future of data as a business asset and liability.   Discover how data value and data risk if employed strategically can be utilized to accelerate business “ethics” in a data saturated world.

In this session, topics of discussion will include:

  • The future of data as a business driver
  • Best practices for handling data
  • Ethics in data management

Moderator:

Stephen SkinnerVisual Data ArchitectDataBilder

Panelists:

Jordan MorrowGlobal Head of Data LiteracyQlik

Amy BishopDirector of StrategyHawkeye

Charles Mueller, Ph.D.Data Scientist Rackspace Technology

11:50 AM - 12:20 PM ET

Data Science Strategy & Leadership - (Track 1)

USE CASE: A Guide to Building a Data Driven Culture

When it comes down to it, organizations struggle with becoming data driven and making it a part of their culture. Hiring a team of data scientists does not fix this problem outright. Success is dependent upon building the right processes, democratizing data and resetting the mentality across the organization. These problems are often more difficult to solve than the tech and math related to data science. Join us in the discussion of a how to guide for building a data driven culture.

In this session, topics of discussion will include:

  • Understand the data maturity model and where to start. 
  • Get an overview of processes and people requirements to drive a data driven culture. 
  • Understand the citizen data scientist movement and the realistic expectations of people outside of data science

Daniel GremmellHead of Data SciencePolicygenius

11:50 AM - 12:20 PM ET

Insights & Applications - (Track 2)

USE CASE: The Intuition Behind Machine Learning in Marketing 

Since the year 2013 important breakthroughs and advances in technology have made it possible to run sophisticated predictive models capable of classifying images, text, and sound. Technology has brought to reality self-driving cars, chat bots and a host of other AI powered devices. In this session we will present key insights that will help you make AI/ML more beneficial to your marketing efforts. Through real world case studies, the session will demystify the core technologies around ML and illustrate how to successfully apply the technology. 

In this session, topics of discussion will include:

  • How to think and interpret predictive models   
  • What metrics we use to evaluate models 
  • Specific case studies in optimization, channel attribution

Mario A. VinascoDirector BI and Analytics Credit Sesame

12:25 PM - 1:10 PM ET

Data Science Strategy & Leadership - (Track 1)

USE CASE: Explainable Artificial Intelligence (XAI) 

Deep learning algorithms have achieved high performance accuracy in many complex domains. Due to the nested non-linear structure of deep learning algorithms, these highly successful models are usually applied in a black-box manner, i.e., no information is provided about what exactly causes them to arrive at their predictions  Explainable Artificial Intelligence (XAI) creates interpretable models while maintaining a high level of learning performance, thereby enabling users to understand, appropriately trust the underlying models. The session will provide a comprehensive overview of XAI concepts along with three use case demonstrations across biomedical, natural language processing and security applications.

In this session, topics of discussion will include:

  • Creating interpretable models while maintaining high accuracy
  • How to leverage explainability to increase trust in model decisions?
  • How XAI enhances understanding of “black box” models & feature engineering?

Sherin MathewsSenior Data ScientistMcAfee

12:25 PM - 1:10 PM ET

Insights & Applications - (Track 2)

USE CASE: Going Beyond Payments – How Mastercard is Utilizing Data & Analytics Intelligence 

In this session you’ll hear fascinating use cases based on Mastercard’s cumulative experience in partnering across industries.  Discover how they have successfully produced valuable market and customer insights using a rich combination of data sets and analytical approaches.

In this session, topics of discussion will include

  • Cross-industry application on data & analytics
  • Insights about observable markets and consumer trends
  • Application of data analytics and marketing science to improve MROI, customer experience and value proposition innovation

Carlos Jose Fonseca SVP Data & Services. Sales Strategy and Solutions FinancialMastercard

1:10 PM - 1:25 PM ET

Afternoon Break

1:25 PM - 1:55 PM ET

Data Science Strategy & Leadership

USE CASE: Applied ML ROI – Understanding ML ROI From Different Approaches at Scale

Solving hard business problems increasingly requires operationalizing ML at scale and that makes understanding the costs directly associated with that effort even more important. Knowing the direct costs of the ML effort being undertaken allows a better understanding of the potential return on investment (ROI) model during the decision making process. Having a solid ML strategy for the organization allows that decision making process to happen in a definable and repeatable way. Getting to that point for an organization takes planning and practice. That includes understanding how to match the deep understanding of subject matter experts to the technical application of ML programs. Understanding applied machine learning models with strong potential return on investment strategies helps ensure a definable and repeatable process remains an outcome of the organizations ML strategy.

This presentation focuses on examining three examples including Google Cloud Vision APIs, TensorFlow Serving on Microsoft Azure, and TensorFlow Serving on premise.

 

Dr. Nels LindahlDirector, Clinical Decision SystemsCVS Health

2 PM - 2:45 PM ET

Data Science Strategy & Leadership - (Track 1)

PANEL DISCUSSION: Addressing Bias in AI: How “Woke” Are Your Algorithms?

Data leaders are acutely aware of bias in data collection and they are wrestling with effective ways to ensure that their data processes are bias free. Join us for a conversation about bias and how leaders are navigating this major data quality issue.

In this session, topics of discussion will include:

  • Reducing bias in machine learning
  • How to handle explainability
  • Data governance

Moderator:

Joe FleischerEditorial Director, Finance ChannelArgyle Group

Panelists:

Dr. Wade Schulz, MD, PhDAssistant Professor of Laboratory Medicine & Computational Healthcare ResearcherYale School of Medicine

Dimple ThakkarFounder of Pradime LLC & Former Head of EPMO Resource Development BlueCross BlueShield

2 PM - 2:45 PM ET

Insights & Applications - (Track 2)

FIRESIDE CHAT: Scoring Big with Big Data – How Data is Transforming the Sports World

Data is the name of the game in the modern sports world. From ticket sales, to player training methodology, to real-time delivery of player stats to the consumer, data is the common denominator behind the enhanced sporting experience.

David Michael, former CTO of XFL (startup American football league which was forced to shut down earlier this year due to COVID), engages in conversation with Vince Ryan, Editor-in-Chief at CFO Magazine, to shed light on how professional sports leagues like the XFL leverage data to improve every aspect of the game.

In this session, topics of discussion will include:

  • Data as a business driver in sports.
  • The ways in which we can use data to maximize an athlete’s performance.
  • How the XFL incorporated a “cloud first” approach to deliver real-time data to consumers to enhance their overall experience.

David MichaelFormer CTOXFL

Vince Ryan Editor-in-ChiefCFO Magazine

2:45 PM - 3 PM ET

Afternoon Break

3 PM - 3:30 PM ET

Data Science Strategy & Leadership - (Track 1)

USE CASE: Application of Image Based KNN and Anomaly Detection to Product Type Classification

In e-commerce product catalog, product types have a significant influence on customer journey starting from product discovery. Image-based classification approaches do not have high enough precision by itself to be used in production. On the other hand, text-based classification models are challenged by noisy input data, flattened product type hierarchy, and certain kitchen sink product types. 

By combining image based KNN with anomaly detection, the speaker will demonstrate how to detect product type errors in an unsupervised manner.

In this session, topics of discussion will include:

  • How to use anomaly detection to validate golden data set
  • How to optimize recall/precision of image based KNN
  • How to build end-to-end misclassification detection pipeline for large scale catalog

Binwei Yang, PhDDistinguished Engineer, Merchant Technology Data Science,Walmart Labs

3 PM - 3:30 PM ET

Insights & Applications - (Track 2)

USE CASE: Using ML and AI to Produce Real-Time, Scalable, Informed Decisions 

The ability of ML and AI to provide real-time, scalable decision-making support to executive strategy is changing the business landscape. In the healthcare sector, patient privacy, data interoperability, and high stakes patient health ramifications intertwine to create a challenging environment in which to use advanced computation techniques. Join us to learn how Johns Hopkins Healthcare’s model, Callisto has been instrumental in predicting suitable health management programs for THEIR patients that deliver concrete return on the overall health of the patient.

In this session, topics of discussion will include:

  • The unique challenges within the healthcare sector that other industries can benefit by understanding
  • How the runaway cost structures can be fundamentally inverted by targeting pain points with focused ML/AI
  • How advancements in AI has allowed the healthcare sector to leapfrog into the 21st century as a fully-integrated player in the cyber community

Romy Hussain Director, Healthcare EconomicsJohns Hopkins Healthcare

3:35 PM - 4:05 PM ET

KEYNOTE: The Future Starts Today – Small Changes that will Make Big Differences in Your Analytics Journey

Keynote: The Future Starts Today – Small Changes that will Make Big Differences in Your Analytics Journey

The future of analytics is limitless when seen from the eyes of anyone who is familiar with or works in this subject area. But what about your everyday business users? What about your frontline managers, or data handlers, or anyone who is part of the input/output process? User adoption is critical in the advancement of analytics. Join us in this session as we explore activities you can get started on today that will make a difference in the future of your organization’s analytics journey.

In this session, topics of discussion will include:

  • The paradox of “there are no bad questions”
  • The FUD factor
  • The “problems with data”

Lydia WuHead of Talent AnalyticsPanasonic

4:05 PM - 4:10 PM ET

Closing Remarks
 

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Opening Remarks

11 AM - 12:30 PM ET

Lab: Exploring the Race to Capitalize on Untapped Big Data Reserves to Develop Smarter, Data-driven Decisions

AI solution reliance on modern socio-economic trends is one of the most provocative factors for data-driven analytics. Businesses are relying on insights extracted from Big Data, substantiating data as the new form of currency.

This paradigm shift has corporations racing to capitalize on their untapped big data reserves to develop smarter, data-driven decisions capable of improving every business aspect. The complexity of moving to data-driven frameworks is often underestimated. HPE’s AI-driven Full Stack Data Science program works strategically to develop custom, high performing, end-to-end, real-time analytics solutions focused on facilitating client’s success making intelligent, data-driven decisions from their amassed data.

Key take-a-ways:

  • Learn how AI-Driven Full Stack Data Science pipelines power the Extreme-scale Market
  • Explore the real costs associated with Free and Open Source Software
  • Understand how Commercial Products offset many development complexities

Theresa MelvinChief Architect, AI-Driven Big Data SolutionsHewlett Packard Enterprise

12:30 PM - 12:35 PM ET

Closing Remarks

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