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Conferences / Disney Data & Analytics Conference

DDAC 2026

Sep 14–16, 2026 · Disney's Coronado Springs Resort, Lake Buena Vista, FL, United States

Conference
Disney Data & Analytics Conference Vendor & industry
Dates
Sep 14, 2026 – Sep 16, 2026
Venue
Disney's Coronado Springs Resort
Place
Lake Buena Vista, FL, United States
Format
In person
Status
Past
Attendance
—
Homepage: 'over 2,500 executives, managers and analysts representing more than 250 organizations' (generic marketing copy).
Website
disneydataconference.com
Recorded
52 sponsors · 43 speaker appearances
Notes
Sept 14 Training Day, main conference Sept 15-16. Keynotes include Matt Parker, Eric Siegel and Coca-Cola/Disney partnership marketing leads. Speakers: all speakers on the official speakers page (Sept 10, 2026 snapshot); affiliations derived from titles; abstracts truncated. Sponsor tiers (Platinum Plus, Platinum, Gold, Silver, Showcase, Exhibitor) listed without prices; details on request.

Ticket prices

TicketPriceValid untilNotesSource
Super Early Bird (individual and group)$2,499Mar 6, 2026web.archive.org
Group Early Bird per person (3+)$2,599Jul 31, 2026web.archive.org
Early Bird (individual)$2,799Jul 31, 2026web.archive.org
Training Day (one course)$825—web.archive.org
Training Day (two courses)$1,500—web.archive.org
Group per person (3+)$2,799—web.archive.org
Individual (regular)$2,999—After Jul 31, 2026web.archive.org

Sponsors 52

Title / headline 2

Platinum 2

Other 28

Speakers and talks 43

SpeakerCompanyRoleTalkLinks
Amir RozwadowskiAT&TKeynoteThe Invisible Blueprint - How Data, Connectivity and Trust Power Tomorrow's Experiences—
Chase AbrahamThe Coca-Cola CompanyKeynoteRefreshing Adventure Awaits: Disney & Coca-Cola—
Chris LisciandroThe Walt Disney CompanyKeynoteRefreshing Adventure Awaits: Disney & Coca-Cola—
Eric SiegelColumbia UniversityKeynotePredictive AI’s Big Moment: How It Makes Generative AI Reliable—
Josh NationsThe Coca-Cola CompanyKeynoteRefreshing Adventure Awaits: Disney & Coca-Cola—
Marc WilsonAppianKeynoteBridging the Operational Intelligence Gap—
Matt Parker—KeynoteAdventures in Writing Terrible Code—
Prabhath NanisettySnowflakeKeynoteBridging the Operational Intelligence Gap—
Tim FinleyCouchbaseKeynoteBlurred Lines and Clear Vision:  The Future of Data and Analytics—
Alexander VolfovskyDuke UniversityFeaturedThe Christmas Movie Playbook for Green-Lighting Analytical Projects—
Angela AlexanderThe Walt Disney CompanyFeaturedDisney Compass: Charting a New Course in Data Collaboration and Audience Insights—
Ben ThompsonCursorFeaturedMove Faster with Agentic Data Workflows—
Beth AlbrightPixar Animation StudiosFeaturedThe Human Behind the Science: Judgment, Creativity and Perspective in Human-Centered Analytics—
Bianca PryorNVIDIAFeaturedThe Private Artificial Intelligence Blueprint: Accelerating Enterprise Deployment with Cloudera, Dell and NVIDIA—
Bill RandNorth Carolina State UniversityFeaturedLevel Up Your Coding: Productization in the World of Artificial Intelligence—
Bj PriceThe Walt Disney CompanyFeaturedThe Society of Curious Analysts Presents: A Field Guide to AI Curiosities, Artifacts and Nonsense—
Brandon RamseyESPNFeaturedFrom Heuristics to Modern ML: ESPN's Incremental Path to Intelligent Recommendations—
Celia GomezThe Walt Disney CompanyFeaturedThe Human Behind the Science: Judgment, Creativity and Perspective in Human-Centered Analytics—
Chad CooperThe Walt Disney CompanyFeaturedEverything I Know Is Wrong, Trust Me—
Chris SzydloDisney InstituteFeaturedDisney's Approach to Employee Engagement—
David DichmannClouderaFeaturedThe Private Artificial Intelligence Blueprint: Accelerating Enterprise Deployment with Cloudera, Dell and NVIDIA—
Emily KubicekThe Walt Disney CompanyFeaturedDisney Compass: Charting a New Course in Data Collaboration and Audience Insights—
Gary CrupiIBMFeaturedGame, Set, Data: The Architecture Behind Real-Time Insights at the U.S. Open—
Jaclyn MathaiDisney EntertainmentFeaturedThe Human Behind the Science: Judgment, Creativity and Perspective in Human-Centered Analytics—
Jacob BenoitThe Walt Disney CompanyFeaturedLarge Language Model Evaluation and Guardrails: Building Trustworthy Artificial Intelligence Systems—
Jeff CammWake Forest UniversityFeaturedLarge Language Model Evaluation and Guardrails: Building Trustworthy Artificial Intelligence Systems—
John LopusAnthropicFeaturedThe Arc Toward Managed Agents: Running Artificial Intelligence Agents as Infrastructure—
Julie Holt BenthamDisney PublishingFeaturedThe Human Behind the Science: Judgment, Creativity and Perspective in Human-Centered Analytics—
Katerina Iliakopoulou-ZanosESPNFeaturedFrom Heuristics to Modern ML: ESPN's Incremental Path to Intelligent Recommendations—
Kristen SwerzenskiThe Walt Disney CompanyFeaturedI'm Not a Data Scientist...Right? A Field Guide for 'Unofficial' Data Professionals—
Kyle LindseyWorld Wide TechnologyFeaturedThe Architecture of an Intelligent Venue—
Max BentonThe Walt Disney CompanyFeaturedThe Christmas Movie Playbook for Green-Lighting Analytical Projects—
Michelle McGuireDeloitteFeaturedHow Deloitte Brings Magic to the Olympic and Paralympic Games—
Paul ParkinsonOracleFeaturedMemories are the Magic: Building AI that Remembers—
Peter MantaInformaticaFeaturedThe Agentic Data Contract: Redefining Data Readiness for Autonomous Decision-Making—
Rachel ChungCarnegie Mellon UniversityFeaturedThe Society of Curious Analysts Presents: A Field Guide to AI Curiosities, Artifacts and Nonsense—
Rebecca GodsilDisney InstituteFeaturedDisney's Approach to Employee Engagement—
Rebekah LindborgThe Walt Disney CompanyFeaturedI'm Not a Data Scientist...Right? A Field Guide for 'Unofficial' Data Professionals—
Rick HoulihanOracleFeaturedMemories are the Magic: Building AI that Remembers—
Shayde ChristianClouderaFeaturedThe Private Artificial Intelligence Blueprint: Accelerating Enterprise Deployment with Cloudera, Dell and NVIDIA—
Tae Hong MinThe Walt Disney CompanyFeaturedLarge Language Model Evaluation and Guardrails: Building Trustworthy Artificial Intelligence Systems—
Tara SteuberThe Walt Disney CompanyFeaturedLevel Up Your Coding: Productization in the World of Artificial Intelligence—
Vasudha KhareConfluentFeaturedYour Model is Fine, Your Context Might Be Broken—

Sources