CDAO Executive Summit 2019

W Atlanta-Midtown, Atlanta, GA
September 22, 2019 - September 24, 2019

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Welcome to Opal Group’s CDAO Executive Summit

Leveraging Data and Analytics to Drive Value and Optimize Decision Making

The CDAO Executive Summit is a gathering of C-Suite Executives and Senior Decision Makers from Fortune 1000 and leading enterprise organizations. Our intimate, invitation-only event creates new business relationships and opportunities to benchmark with true peers while focusing on key business challenges.

Our summit provides a specialized, strategically-built experience featuring unparalleled speaking sessions, on and off-site networking opportunities, and customized face-to-face business meetings.

We believe in creating a memorable, collaborative and effective experience focused on continuous improvement for Chief Data & Analytics Officers, Chief Data Officers, Chief Analytics Officers, and other top executives in data, analytics, artificial intelligence, business intelligence, IT and data governance.

Join us! Interested in attending, speaking or sponsoring? Contact Cherlene Willis at (212) 532-9898 ext 230 or email info@opalgroup.net.

The Summit Experience - Hear from Starbucks, Expedia, Home Depot, and more!



Current as of September 23, 2019

Speakers

Inderpal Bhandari, Global Chief Data Officer, IBM Corporation

Dr. Vijay Gandapodi, Global IT head – Marketing Analytics & Data Science, The Coca-Cola Company

Michael W. Simon, Chief Analytics Officer, Central Intelligence Agency

Dr. Saket Kumar, Chief Data Scientist – Global Premium Services, Google

Adam Blum, CEO, Auger.AI

David Mathison, CEO, CDO Club

Andrew Sohn, CDAO (Former), Crawford & Company

Heidi Lanford, Vice President, Enterprise Analytics & Data, Red Hat

Pradipta Saha, Head of Data & Analytics (Global Supply Chain), Mondelez International

Jim Young, SVP Information Management & Analytics, Travelers Insurance

Charles Li, IT Chief Data Officer for Trading, Supply & Midstream, Shell

Alan Stukalsky, Chief Digital Officer, Randstad North America

Alan Segal, Vice President of Audience Development & Analytics, CNN

Santosh Kudva, Vice President of Data & Analytics, GE Power

Ash Dhupar, Chief Analytics Officer, Publishers Clearing House

Jerry Gupta, SVP, Digital Catalyst, Swiss Re

Raja Chakarvorty, VP Data Science, Protective Life

Danial Dashti, Senior Machine Learning Scientist, Amazon

Kathleen Maley, Sr. Director of Consumer & Digital Analytics, KeyBank

Srini Sankar, Enterprise Data Leader, Hanover Insurance

Juan Gorricho, SVP of Data & Analytics (Former), TSYS

Colin Coleman, SVP Data & Analytics, Equifax

Tim Eisenmann, Chief Analytics Officer and Senior Vice President of Advanced Analytics, American Tire Distributors

Amitha Krishnappa, Sr. Manager, Analytics, Measurement & Optimization, Walmart Labs

Pat McCleary, Head of North America Call Center Data & Analytics, TD Bank

Anuj Marfatia, Director, Business Analytics, Brunswick Corporation

Eric Little, CEO & Co-Founder, LeapAnalysis

Bill O’Kane, VP & MDM Strategist, Profisee

Brian Keare, Chief Information Officer, Incorta

Diwakar Goel, VP, Global Chief Data Officer, GE

Mark Gelhardt, VP Technology Governance, U.S. Bank/Elavon

Prakhar Mehrotra, Senior Director, Machine Learning, Walmart Labs

Armen Kherlopian, Chief Science Officer, Genpact

11:00AM

Welcome Brunch | Event Registration

11:45AM

Chairperson’s Opening Remarks

Presented by

David Mathison, CEO, CDO Club

12:00PM

Opening Keynote Presentation

 

Leveraging Advanced AI to Give Your Company a Competitive Edge

 

This session will cover the impact of data science on regional GDP per capita. During this session we will discuss the following Advanced AI topics and how they are impacting economics and company performance.

  • Reinforcement Learning
  • Recommendation systems
  • Segmentations
  • Deep Learning
  • GAN
  • Transfer Learning
  • Multitask Learning

 

During the presentation, we will identify the hurdles to implementing this system and what needs to be done for these solutions impact financials. We will cover why these systems are not adopted and absorbed by the end users, and what process needs to be put in place to make these product launches successful.

Presented by

Dr. Vijay Gandapodi, Global IT head – Marketing Analytics & Data Science, The Coca-Cola Company

12:35PM

Interactive Panel Discussion

 

Building Data Centricity  – Implementing MDM to Ensure that Your Data is Coordinated and Synchronized

 

With the recent explosion of big data, analytics and IoT, the consistency of referencing and applying high-quality master data has become mission critical. Your organization has to make sure it has its key data assets
efficiently and accurately managed, and also needs to embrace new data assets to fully realize the economic potential – by joining or referencing the existing master data that the company already owns. MDM should be an essential part of any company’s data strategy, and should be forward-looking with long-term commitment.

 

Join us in this thought-provoking panel discussion as we discuss the steps necessary for a successful MDM implementation, such as:

  • Ensuring that your data collection is aligned with your business goals
  • Establishing Data Governance that will be embraced by the entire organization
  • Applying MDM to new data additions or new applications
  • Fostering an environment where data is driving the real decisions
  • Leveraging the MDM capability to manage existing and legacy systems by establishing a roadmap with multiple phases
Moderator

Bill O’Kane, VP & MDM Strategist, Profisee

Panelists

Diwakar Goel, VP, Global Chief Data Officer, GE

Andy Sohn, Chief Data & Analytics Officer, Crawford & Company

Raja Chakarvorty, VP Data Science, Protective Life

Charles Li, IT Chief Data Officer for Trading, Supply & Midstream, Shell

1:30PM

One-on-One Business Meetings | Networking Break

2:35PM

Keynote Presentation

 

Creating an Effective and Diverse Data and Analytics Team

 

Building data and analytics teams is a competitive endeavor yet one executive has found success in rounding out his data team by developing a conglomerate of data specialists. Once core functions are identified, learn how to equip your team for deeper skills and greater growth.

 

In this session you’ll learn:

  • How to identify core functions that allow for scalability
  • The resources data teams need in order to be successful
  • Modern approaches to evaluating qualifications and aptitude
Presented by

Juan Gorricho, SVP of Data & Analytics (Former), TSYS

3:10PM

Keynote Presentation

 

AI Is Eating Software: How A Second Generation of AutoML Tools Enables Enterprises to Build Predictive Models into Their Applications

 

The first generation of Automated Machine Learning tools (from DataRobot, H20, Auger.AI and others) enables data scientists and business analysts to train with thousands of algorithm and hyperparameter combinations to generate the best possible predictive models. After uploading the data as a spreadsheet and waiting for training, the user selects the best model from the leaderboard and they are ready to do predictions.

 

Recently, several new AutoML products (from Google Cloud AutoML Tables, Microsoft Azure AutoML and Auger.AI’s open source A2ML API) have introduced the ability to automate the full AutoML process. Their APIs each support several phases in a pipeline: Importing Data, Training Against Algorithms and Hyperparameters, Evaluating Models, Deploying Models, Predicting Against New Data, and finally Reviewing the Performance of Models. These products all emphasize automated use by developers, not analysts uploading spreadsheets and viewing leaderboards.

 

Now that the full A2ML process can be automated new frontiers in exploiting AutoML’s capabilities are opened. Business logic in applications can be replaced by predictive models automatically generated from any data the developer has access to. Painstakingly coded sorting of results and lists of objects (accounts to manage, contacts to call, devices to maintain, trucks to route) can be ordered by a predictive model ranking. Complex cascades of if-then-else and switch statements (also known as business rules) derived from some “subject matter expert” or business person’s judgment can be replaced by the insights of a predictive model.

This use of AutoML has a far wider audience than just data scientists. Enterprise application developers can be far more productive and the amount of hard coded business logic in applications will steadily be reduced by use of predictive models. Software Has Eaten the World. With second generation AutoML, AI will now eat software.

 

This talk will describe in more detail just what second generation “Automated AutoML” entails. And describe several use cases where we have put this into effect for various applications and business problems.

 

Sponsored by

Baylor University

 

Presented by

Adam Blum, CEO, Auger.AI

3:45PM

Keynote Presentation

 

Ensuring your Data Supports your Organization’s AI Goals

 

There is no AI without IA (Information Architecture)! – When it comes to artificial intelligence (AI), there is no such thing as data overload. In fact, it’s quite the opposite – the more data, the better. However, the data fed into ML and other AI processes needs to be the right data and have certain characteristics. This doesn’t just happen, there has to be strategy and programs in place to provide useful data to AI systems. As the lifeblood of AI, data is critical to helping you get the business insights you need to move your business forward.

 

In this session we will discuss ways to lay the groundwork for a successful data strategy that will maximize the value of AI, such as:

  • Data Strategies necessary to support your business strategies
  • Processes for ensuring go-forward data is suitable for AI
  • Strategies for the best use legacy data with quality defects
  • Understanding the limitation with your data – including bias, ethical use, and regulatory constraints
Presented by

Andrew Sohn, CDAO (Former), Crawford & Company

4:20PM

One-on-One Business Meetings | Networking Break

5:25pm

Interactive Panel Discussion

 

Ensuring the Ethical Collection and Use of Data & Analytics

 

In the wake of last year’s application of GDPR and the multitude of data breaches that have occurred recently, it’s never been a better time for organizations to take a close look and ask hard questions around how they collect, manage, and act on audience data. As the use of data & analytics grows, the potential for ethical dilemmas and reputation risks also increase, so data and analytics leaders have to develop solutions to mitigate these risks.

 

In this engaging panel discussion we will discuss some tips for organizations to protect their customers and their reputations, such as:

  • Not relying too heavily or exclusively on third-party data
  • Be clear right up front with what data you will be collecting and how your organization will use it
  • Ensure transparency with your customers to gain their trust to create greater brand loyalty and increased revenues
  • Know the origins of your data and the rules surrounding it
  • Put processes in place to understand the permissions associated with the data you hold, and mitigate the risk of misuse
Moderator

TBD

Panelists

Jim Young, SVP Information Management & Analytics, Travelers Insurance

Srini Sankar, Enterprise Data Leader, Hanover Insurance

Jerry Gupta, SVP, Digital Catalyst, Swiss Re

Mark Gelhardt, VP Technology Governance, U.S. Bank/Elavon

6:15PM

Networking Cocktail Reception & Hors d’oeuvres

7:45AM

Networking Breakfast

8:25AM

Chairperson’s Opening Remarks

Presented by

David Mathison, CEO, CDO Club

8:30AM

Opening Keynote Presentation

 

Making Data Work for You: Turning Data into Insights

 

Every day the world around us gets digitized as text, audio, and video result in an enormous amount of data being generated. What is scarce in this abundance is the information that can improve our decision-making. Business leaders often feel overwhelmed by the amount of data headed their way. The task of extracting useful information requires a combination of computer science, statistics & modeling, domain knowledge, and communication skills. Google has been using a number of data sets, tools and data science methods to help business leaders make better decisions.

 

Making a tangible impact on many business challenges often has little to do with the data – join us in this informative session as we review the best approaches that have been utilized to improve decisions.

Presented by

Dr. Saket Kumar, Chief Data Scientist – Global Premium Services, Google

9:10AM

Keynote Presentation

 

Leveraging People, Processes and Tools to Overcome “Data Quicksand” and Develop Truly Impactful Analytics

 

They make it sound good during the interview… “Hey, come join our company. You’ll really make an impact. Analytics are huge and you’ll be leading our efforts!” It’s very persuasive. You take the bait… And then reality hits. You’re spending 90% of your time on just finding the data, cleansing the data, and just getting it ready for the analyst team. This isn’t what you signed up for. You’re not changing the world. But you could be.

 

Join this session with industry luminary Brian Keare who cracked the code at Nortek and learn the secrets to turning the problem on its head and spending that 90% on truly impactful analytics work instead of just 10%. And maybe, just maybe, changing the world in the process.

Presented by

Brian Keare, Chief Information Officer, Incorta

9:45AM

One-on-One Business Meetings | Networking Break

10:45AM

Interactive Panel Discussion

 

Developing Innovative and Creative Strategies to Attract, Develop and Retain Data and Analytics Talent

 

Few areas of the IT job market have seen the growth and disparity in supply and demand that the data and analytics field has experienced. As big data continues to get bigger and the analytics field continues to mature, it’s becoming a core part of business and the decision-making process. Competition for top analytic talent is going to be fierce as more companies enter the hiring fray. In addition, schools and universities are still lagging behind as it relates to teaching the skills necessary to fill these data and analytics jobs, so it’s critical for organizations to develop internal programs or partner with schools to offer courses in these areas.

 

In this panel we will discuss strategies for improving talent acquisition and development, such as:

 

  • Knowing the specific data and analytical skills you are hiring for
  • Creating career paths that lead to high-profile positions within the organization
  • Illustrating the business impact that data and analytics can create
  • Showing data and analytics talent that the organization, particularly senior management, is excited about the impact data and analytics has on the business
  • Fostering a culture of self-development within the data and analytics teams
Moderator

Michael Galvin, Metis

Panelists

Pat McCleary, Head of North America Call Center Data & Analytics, TD Bank

Alan Stukalsky, Chief Digital Officer, Randstad North America

Colin Coleman, SVP Data & Analytics, Equifax

Kathleen Maley, Sr. Director of Consumer & Digital Analytics, KeyBank

11:40AM

Keynote Presentation

 

Deploying Machine Learning Models in Production

 

The deployment of machine learning models describes the process of making the models available in production environments, where the predictions can be accessed by other systems. Join this informative session as we will discuss things to consider to have a successful ML deployment pipeline, and address the following obstacles:

  • Data Interdependability: Change in any input feature may change the importance, weight or the usefulness of the remaining features. This challenge is commonly called “changing anything changes everything” issue
  • Data Stability: In an ML System, there are two equally consequential components: code and data. Unlike the code, some data inputs can be unstable and change over time. There needs to be a way to track these changes in order to fully understand the system
  • Pipeline Configuration: Especially when models are constantly iterated on and subtly changed, tracking configuration updates whilst maintaining configuration clarity and flexibility becomes an additional burden
  • Separation of Expertise: Machine learning systems require cooperation between multiple teams. Which can result in no single team or person understanding how the overall system works, teams blaming each other for failures, and general inefficiencies
Presented by

Danial Dashti, Senior Machine Learning Scientist, Amazon

12:10PM

Networking Luncheon

1:15PM

Keynote Presentation

 

Modifying Your Workforce Structure to Ensure a Successful Digital Business Transformation

 

The growing importance of data and analytics creates new strategic challenges for organizations and data and analytics leaders. Now is the time to create an organization with new data and analytics roles fit for the future. Modern business is creating new responsibilities and roles for those managing data and analytics and requires different, complex skills in areas like AI and machine learning. As the transformation toward digital business continues, new roles blending IT and business functions will emerge.

 

In this informative session we will discuss the key roles to focus on for future-proofing your data and analytics workforce, including:

  • Data-driven facilitators to better manage information assets
  • Data engineers to investigate and interpret data variations for early error detection
  • Information architects to improve the structural design of shared information environments
  • Information product managers to help business and information leaders agree on how to effectively

 

Presented by

Tim Eisenmann, Chief Analytics Officer and Senior Vice President of Advanced Analytics, American Tire Distributors

1:50PM

Keynote Presentation

 

Creating a Self-Service Analytics Framework

 

The current generation of business users have grown with the smartphone and social revolution. Unlike the earlier generations, they are more inclined to build the analytics themselves. This poses an interesting challenge in terms of successfully building and deploying a framework to support the self-service needs of our business community. Once we open up our analytics platforms to self-service, the scalability of the framework takes a new meaning and brings its own set of challenges for standards and governance.

In this session, we will share a self-service framework for an industrial organization that includes aspects of:

  • Data availability
  • Technology
  • Training
Presented by

Santosh Kudva, Vice President of Data & Analytics, GE Power

2:35PM

Networking Break | One-on-One Business Meetings

3:40PM

Keynote Presentation

 

Personalizing the Customer Experience to Yield a Higher ROI

 

While the value of personalization is clear, the task can seem rather lofty. Despite the many challenges in creating dozens or even hundreds of different experiences for your customers, it’s imperative to make sure that your message speaks to each of them on an individual level. The organization must deliver real-time contextually relevant experiences that are informed by customer data.

 

Join us in this highly interactive session as we talk about the ways your organization can connect and aggregate data about your customers and their preferences, such as:

 

  • Messaging that encourages active participation and celebrates customer achievements
  • Utilizing information about past interactions and purchases, and retargeting your audience on different platforms
  • Creating compelling and relevant content and experiences that stay with the customer throughout their entire journey
  • Utilizing deep learning technology on industry trends, consumer behavior, and intent signals to ensure that content and messages reach the right customer at the right time in the right format
Presented by

Ash Dhupar, Chief Analytics Officer, Publishers Clearing House

4:10PM

Keynote Presentation

 

Using Data Stories to Explore and Explain How and Why Data Changes Over Time

 

Most data and analytics teams are adept at creating dashboards and visualizations, but many are unfamiliar with wrapping those artifacts into a useful narrative. A narrative that simply describes data would be of limited use for decision makers. It’s the context around the data that provides value and that’s what will make people listen and engage.

 

In this session we will discuss ways to utilize storytelling to encourage and energize critical thinking for business decisions, such as:

  • Creating engagement to develop enticing and relevant stories
  • Acknowledging and defusing human bias in the stories
  • Debating data stories collaboratively within your organization to get higher levels of engagement
  • Subjecting data stories to critical thinking to improve decision making
Presented by

Prakhar Mehrotra, Senior Director, Machine Learning, Walmart Labs

4:40PM

One-on-One Business Meetings | Networking Break

5:45PM

Interactive Panel Discussion

 

Championing Data Literacy to Facilitate a Data Driven Business

 

The pervasiveness of data and analytics capabilities, including AI, requires the creators and customers to speak data as a common language. As data and analytics becomes a core part of digital business and data becomes an organizational asset, employees must have at least a basic ability to communicate and understand conversations about data. In short, the ability to “speak data” will become an integral aspect of most day-to-day jobs. It’s critical for data and analytics executives to essentially create the narrative for data literacy, while also highlighting the business value to be gained.

 

In this session we will discuss the steps necessary to create an effective data literacy program, like:

  • Identifying the fluent and native “data speakers” in your organization who can serve as mediators for the business groups
  • Determining the areas where communication barriers mean that data isn’t being utilized to its full business potential
  • Educating executive leadership and front-line leaders that are involved in crafting and implementing data-driven solutions, products and services
  • Establishing proof-of-concept workshops to capture and review lessons learned, and sharing the lessons with other groups and departments to raise awareness of any literacy gaps
Moderator

Pradipta Saha, Head of Data & Analytics (Global Supply Chain), Mondelez International

Panelists

Eric Little, CEO & Co-Founder, LeapAnalysis

Amitha Krishnappa, Sr. Manager, Analytics, Measurement & Optimization, Walmart Labs

Heidi Lanford, Vice President, Enterprise Analytics & Data, Red Hat

6:30PM

Networking Cocktail Reception & Hors d’oeuvres

8:00AM

Networking Breakfast

8:45AM

Chairperson’s Opening Remarks

Presented by

David Mathison, CEO, CDO Club

8:50AM

Opening Keynote Presentation

 

Leading by Example, Creating a Data and AI-driven Company

 

Leading a Data and AI transformation requires new mindsets and methods at every level; it takes an AI Enterprise culture. In this experience-based session, Inderpal Bhandari will share IBM’s internal experience to help accelerate your own company’s Data and AI journey from data strategy to AI solutions.

 

Join Inderpal in this enlightening session as he will discuss how to:

  • Develop a clear data strategy
  • Execute enterprise-wide data governance and management systems
  • Become the central data source and AI framework
  • Build deep data and analytics partnerships
  • Develop and scale talent
Presented by

Inderpal Bhandari, Global Chief Data Officer, IBM Corporation

9:30AM

Keynote Presentation

 

Human and Machine Intelligence

 

The enormous effort devoted to developing “artificial intelligence” that mimics human decision-making may be misplaced and even counterproductive for many organizations.  For knowledge work, in particular, we should not strive for AI systems to replace humans, since we run the risk of reifying the cognitive and organizational biases that already exist.  Instead, we should harness the power of computers to perform tasks that human experts are not very good at accomplishing (such as situational awareness), leaving more time in the workday for human experts to do what they are good at (thinking creatively and identifying causal relationships).  And by building joint human-machine platforms, we can efficiently share knowledge across an organization and prioritize what additional information to collect.  This approach can also ease the transition from today’s workplace to a future one, by starting with expertise-driven causal explanations and by requiring AI methods to be understandable.

 

In addition to describing a future workflow in which we leverage the best of human and machine intelligence, this presentation also points out the challenges in moving to this future.  Specifically, the presenter will discuss key technical and cultural gaps that will need to be overcome if we are to get greater value out of the data we possess and collect and to enable data-driven decision-making at scale.  These gaps represent priority areas for research funding, which business leaders should support.

 

Presented by

Michael W. Simon, Chief Analytics Officer, Central Intelligence Agency

10:05AM

One-on-One Business Meetings | Networking Break

10:35AM

Closing Panel Discussion

 

Creating a Shared Data and Analytics Vision that Becomes Ingrained in the Corporate Culture

 

Many organizations face continuing challenges when trying to fully adopt big data and analytics processes, but the benefits that are gained by new technology solutions are having a tremendous impact on the application of data and analytics. Companies are having little issue in comprehending the benefits of technology, but the biggest challenge is in the process of cultural change.

 

In this final panel discussion of the event, we will review the issues that need to be addressed in order to implement and maintain a cultural change, such as:

 

  • Identifying the critical business questions that will drive business value and financial impact
  • Considering the critical human and organizational issues that will ensure successful adoption
  • Determining how to leverage big data and analytics in order to effectively drive innovation
  • Adapting and transforming culturally in response to the opportunities and the challenges presented by big data
Moderator

David Mathison, CEO, CDO Club

Panelists

Alan Segal, Vice President of Audience Development & Analytics, CNN

Anuj Marfatia, Director, Business Analytics, Brunswick Corporation

Armen Kherlopian, Chief Science Officer, Genpact

11:20AM

End of Summit | Champagne Toast | Thank you!

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W Atlanta-Midtown
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Please contact your business development associate to reserve your hotel room.



More networking, greater interactions, bigger ROI:

One of the biggest challenges that companies face is standing out from the crowd and getting exposure with executives from leading enterprise organizations. Your company has the perfect solution to your customer’s problem but how do you grab their attention and present your value proposition?

The CDAO Executive Summit is the perfect platform to gain valuable exposure for your brand with exclusive access to key decision makers. The attendees at the Summit are C-Suite Executives and Senior Decision Makers from the Fortune 1000 and are selectively invited and pre-qualified to ensure they carry budgetary responsibility. The event provides a specialized, strategically-built experience for cutting-edge solution providers to engage, interact, and build relationships with executives who are actively looking for new business partners.

Solution providers at the Summit have the opportunity to showcase their brand as a leader in the Data and Analytics field while developing new business relationships through unparalleled speaking sessions, interactive networking events, and custom face-to-face business meetings.

  • Leveraging Data to Give Your Company a Competitive Edge
  • Transition Your Organization into a Data-Driven Culture
  • Leveraging AI to Help to Ensure that Data is a Source of Value for the Organization
  • Overcome Data and Analytics Complexity and Ambiguity to Drive Business Value
  • Building a Successful Data Governance Strategy
  • Creating an Analytically Driven Organization: Implementing an Advanced Analytics Program
  • Developing Innovative and Creative Strategies to Attract, Develop and Retain Data and Analytics Talent
  • Ensuring the Ethical Collection and Use of Data & Analytics
  • Implementing Predictive Analytics to Forecast Revenue and Improve Marketing Campaigns
  • Personalizing the Customer Experience to Yield a Higher ROI
  • Prescheduled One-to-One Meetings:
    Each participating solution provider and attendees will have pre-summit access to our matching software that allows you to completely customize your meeting agenda. The password-protected website provides the information needed to make your selections on who you want to meet with.

  • Exceptional Networking Opportunities:
    We strive to maximize your face-to-face time by providing a multitude of avenues to engage the senior executives in attendance. The agenda incorporates an off-site networking activity, networking luncheons and cocktail reception. Leverage the meeting’s intimate atmosphere to build strong personal relationships with current and future clients.

The CDAO Executive Summit is an invitation-only, exclusive event for heads of data, analytics, business intelligence, IT, artificial intelligence, data science, machine learning, deep learning, information architects and information governance from Fortune 1000 and leading enterprise organizations.

 

Chief Data & Analytics Officers (CDAOs)
Chief Data Officers (CDOs)
Chief Analytics Officers (CAOs)
Chief Data Scientists
Chief Data Architect
SVP/VP/Head of Data Management
SVP/VP/Head of Analytics
SVP/VP/Head of AI, BI & Machine Learning

 

To request your invitation today, please contact Katherine Ilagan at 212-532-9898 ext 233 or email info@opalgroup.net.

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      This experience was amazing. It was personal, conversational and relational. It expanded my knowledge and more importantly, my network. Laura Vostad

      POET, Dir. L&D

      What I enjoyed most was that the number of attendees was big enough to provide me a wealth of information, but small enough to allow me to network with almost everyone at the conference. I walked away with pages of notes, many new contacts and met some great vendors that we will likely do business with in the future. Shelby Pyatt

      Rayonier, VP, HR & IT

      By far, this was the most engaging, value added convening of leaders. It was the right mix of experience, learning, and networking. I absolutely enjoyed the Disney Tour and the book exchange was brilliant. The roundtables were also an added bonus. Sharahn Monk

      Worldpay, US Market Leader, Learning and Development

      Great event, very well organized with relevant speakers and potential business partners. I would recommend to anyone. Shawn Dingle

      Sonic Automotive, Senior Training Director

      OPAL is first class. It was the best Conference that I ever attended from the standpoint of speaker quality, organization, and venue. They really seem to care! John Barbieri

      Sompo International, VP, Human Resources

      I thought the whole conference was so well run and that the OPAL team did an amazing job. I would definitely love to attend another event! Tennille Boyer

      Blue Ocean Brain

      Excellent line-up of speakers Connie Keys

      Campbell Soup, Head of Culture & Learning