CDAO Chicago
Presentations
Keynote Presentation: From Data Analyzer to Decision Enabler to Business Driver: How to Elevate Your Organization’s Data Analytics Maturity
- Examine the current maturity of your data analytics capabilities
- Articulate the end goal of a data-driven organization
- How to implement the transformation roadmap with actionable phases
Jason Wang, Chief Risk Officer & VP Data Analytics
Allstate Insurance
Keynote Presentation: Cheese and Change: The Art of Meeting People Where They Are
How a pizza analogy ignited a data-driven transformation
Come join me as I share how we have succeeded in evolving our financial data consumer’s relationship with data!
- Cutting through the noise when setting a strategy
- Staying on the critical path during execution
- Evaluating impact: how to know whether you’re moving the needle
- …and other corporate catchphrases
Jeannie Furlan, VP Financial Data Strategy
Mutual of Omaha
Keynote Presentation: AI is Changing the Relationship Between Data and the Business, as CDO/CDAO Are You Ready?
- How to support the transition from decision support (charts and graphs) to decision automation (models)
- Managing accountability for the Amplified Value and Amplified Risk of AI (AI Governance)
- Scaling AI despite unprecedented operational complexity (AI Change Management)
- How to embrace the CDO/CDAO responsibility as the Enterprise AI leader (AI Portfolio Management)
Dr. Ram Singh, Chief Data Officer
Night Market
Keynote Presentation: Building Data Products in a Data Mesh Architecture to Drive Growth and Customer Value at Scale
- 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? data-enabled innovations, and a world-class data stack to win customers’ hearts, minds and loyalty
Patrick O’Halloran, Solutions Architect WhereScape
Keynote Presentation: Reflections from the AI Integration Frontline
Navigating the complexities of AI integration requires a deep understanding of both its potential and its limitations. This session offers a candid exploration of AI's role in modern data strategies, emphasizing the importance of discerning genuine value from mere hype. Through real-world examples and insights from the frontlines, we'll explore how organizations can strategically harness AI to enhance business outcomes without falling victim to the allure of cutting-edge technology for its own sake. Attendees will learn to cultivate a pragmatic approach, ensuring that AI initiatives align with their organization's goals and data capabilities, leading to sustainable, impactful advancements.
- Recognize the limitations of current AI technologies and avoid overestimating their capabilities in solving complex business problems.
- Develop a critical approach to AI outputs, emphasizing the importance of domain knowledge and fact-checking to prevent misguided decisions.
- Foster a culture of data literacy and collaboration to maximize the effectiveness of AI and automation in driving business value.
- Build a balanced AI strategy that combines foundational preparation with agile implementation, avoiding the pitfalls of perpetual planning or hasty execution.
Jordan Burger, Lead Researcher, AI Applications
Keboola
Keynote Presentation: Bolting Ahead: Precision with Purpose using Artificial Intelligence/ Machine Learning
- Start with the business problems and then identify a technology solution
- Employ machine learning to drive strategic business value and augment business operations
- Actively engage stakeholders to maximize impact and warrant successful products
Hardi Gokani, Director of Product Engineering - AI/ ML
Grainger
Keynote Presentation: Developing a Multidisciplinary Workforce Skilled in Collaborative AI
- Building AI infrastructure and training resources
- Crafting multi-modal AI/ML tools and tutorials to enhance capabilities in analyzing complex data
- Cultivating environments of collaboration and innovation
Yuan Luo, Chief AI Officer
Northwestern University
Keynote Presentation: Beyond the Real: How Synthetic Data Fuels the Future of AI and Generative AI
- The Data Bottleneck: Challenges of Real-World Data for AI/GenAI
- The Rise of Synthetic Data: Crafting Artificial Reality for AI
- Unlocking the Potential: Applications of Synthetic Data in AI/GenAI Growth
Gokula Mishra, Vice President, Data Science
Direct Supply
Keynote Presentation: Morningstar: Accelerating Insight Creation Using Data Mesh
- Initial challenges and motivations for adopting Data Mesh
- Steps taken to transition from traditional data architecture to Data Mesh
- How Data Mesh has accelerated insight creation at Morningstar
- Key lessons learned and best practices
Anne Homsy, Director of Analysis
Morningstar
Anusha Dwivedula, Director of Technical Product Management | Enterprise Data Platform
Morningstar
Keynote Presentation: The Optimal Team Make-up: What is the Talent Set that Every Data & Analytics Leader Should Have, and How To Get Them
- What profile and skillsets do you truly need and how do you combine them to optimize performance? How are data analytics leaders dealing with the great resignation, or the great re-shuffle?
- Identify, upskill and retain internal talent; how to create compelling career paths
- Tapping into collaboration networks – externally, for recruitment and project-based initiatives, and internally, to leverage mobility opportunities
- Nurturing diverse internal talent that could be interested in moving to data analytics roles
Jyoti Mishra, Sr. Director Analytics Executive
Amtrak
Keynote Presentation: Building a Data-Inspired Culture to Drive Better Decisions
- How to build trust in the data and deliver value
- Avoiding paralysis by analysis
- Becoming more hypothesis minded and understanding the "why"
Cyril Nigg, Senior Director Analytics
Reverb
Keynote Presentation: “Sharing the Right Data at the Right Time”: How to Successfully Implement a Smart Data Fabric Integration
- Outlining the core principles of Smart Data Fabric Integration
- Best practices for implementing it
- What role data fabric will play in your data management?
- The Journey of Harris Associates
Rajib Nandi, Head, Head of Data Analytics
Harris Associates