Sadie St. Lawrence, Founder & CEO, Women In Data

• How can leaders capture the full potential of big data and advanced analytics?
• Best practices for technology transformation and methods to optimize value.
• Cultural approaches to empower decision-makers to act quickly, intelligently, and confidently to achieve mission goals.
  

Don Gray, Chief Enterprise Data & Analytics Officer, Mercy Health

As a data and analytics leader, you understand how critical it is to continually keep up to date with the latest capabilities and trends in Data. Should you modernize or monetize your business? Or both? We'll share seven steps to help you find the most efficient time to value your data, so you get it right the first time. 

Thomas Barton, Head of Data Practice, Cognizant Consulting

• Ensuring your analysts thrive rather than survive in the data trenches
• What is the makeup of your ideal data team – defining their roles
• Innovative ways you’re sourcing and training talent – recruiting & retaining
  

Moderated By:

Brady Cole, Chief Data Officer, Bank of the West

Panelists:

Veena Nayak, Vice President of Data Science – Strategy & Solutions, Univ. Of Phoenix

Marcos Martins De Souza, Head of AI & Advanced Analytics, Ally

Sid Mehrotra, Sr. Vice President of Data Science & Analytics, Citigroup Bank

Sam Marks, Director of Strategy & Analytics, Arizona Coyotes

Saptarshi Sengupta, Sr. Director of Product Marketing, Denodo 

• Make the business case to implement AI where it’s needed within your organization
• Optimize decision-making at the executive level
• Track consumer behavior, analyze data and predict business trends
• Create a culture of trust
  
  

Robin Mobasseri, Head of AI Platforms Experience, Wells Fargo

• How do you go about prioritizing which data to bring under governance? What are the best strategies?
• Why does everyone in your organization need to be a “Data Steward”
• How does data governance impact data literacy?

Moderated by:

Sadie St. Lawrence, Founder & CEO, Women In Data

Panelists:

Marcos Martins De Souza, Head of AI & Analytics, Ally

Brady Cole, Chief Data Officer, Bank of the West

Danielle Cloud, Sr. Vice President of Enterprise Data Governance & Platforms, American Express

Roundtable 1A: The Business of Business Intelligence – Designing Agility to Increase Business Performance

• How to consider business data analytics from the business perspective
• Empowering business leaders to create reports and find answers in real-time without relying on IT
• Ensuring your solution’s success and building in continuous process improvement.

Contributors:

Jeffrey Yau, Global Head of Data Science & Analytics, Amazon Music

Sam Marks, Director of Strategy & Analytics, Arizona Coyotes

Jon Mitchell, Regional Sales Director - Americas SW, Qlik

Roundtable 1B: Navigating the Great Resignation – Reskilling & Retaining Data Analytics Talent for Success

• What steps have you taken to upskill your data and analytics teams? How are you filling these roles?
• How do you know your reskilling efforts are paying off?
• How are you aligning individual learning with organizational goals?
• How are you getting them comfortable with the tools, methods, and technology?
  

Contributors:

Robert Merritt, Chief Enterprise Officer, General Assembly

Paul Wu, Principal Data Scientist, Genentech

Monish Balasundaram, Head of Analytics Product Management, Amazon

• Building a cutting-edge data organization that attracts, excites, develops and retains exceptional and diverse talent
• Generating sustainable value with industry-leading data products, insights and expertise
• Increasing efficiency by giving data product teams with end-to-end responsibility in a data mesh architecture
• What’s next?: democratizing data, data-enabled innovations, and a world-class data stack to win customers’ hearts, minds and loyalty
  

Sebastian Klapdor, Chief Data Officer, Vista

Jeff Traenkner, Principal - Customer Success, TheMathCompany

Arun Giri, Head of Platform Engineering & Enterprise Architecture, Union Pacific Railroad

• The most common mistakes organizations make when establishing new AI/ML projects and how to avoid them.
• Implementing a program approach to build valuable AI that Includes constant iteration.
• How to ensure you have the right KPI’s, resources and expertise from the start.

Justin Lo, Head of Data Science & Analytics, Chevron

• When should you consider a move to the Cloud? Is having your ENTIRE enterprise on the cloud a reality?
• Having a strategy in place – creating a clear and feasible plan for the move
• Is your workforce trained and ready to lift and shift?
  

Moderated by:

Sadie St. Lawrence, Founder & CEO, Women In Data

Panelists:

Ben Donlon, Chief Analytics Officer, Metro United Way

Sean Xu, Vice President of Information Management, MGM Resorts

Awah Teh, Chief Data Architect, Capital One

Roundtable 2A: What A Mesh! Choosing Between Centralized & Decentralized Model

In the ongoing “centralization v. decentralization” back and forth, there’s no clear answer…and maybe that’s because elements of both are needed!

• Determine which supports your most critical business practices - the reality of a Hybrid model
• Technical agility and the availability of tools through SaaS providers
• Having the ability to determine if it’s good data or the right data
• Who will benefit the most from this hybrid?

Contributors:

Jennifer Mezzio, Managing Director & Divisional Data Officer - HR, Silicon Valley Bank

Amar Lingam, Head of Enterprise Advanced Analytics & Data Science/AI, CDW

Roundtable 2B: How to Ensure Ethics in AI to Promote Positive Impact Across Your Business Ecosystem

Ethical and responsible data design for AI is central to an enterprise’s strategy and is the best way to make a positive impact for future generations.

• Earning trust and gaining credibility within the organization
• Understand how data cultures need to fit into both business and IT teams
• How does the design of your AI strategy impact your customers?
  

Contributors:

Michelle Bonat, CTO – AI/ML, J.P. Morgan

Stacy Hobson, Vice President of Global Sales Engineering, H2O.ai