10:45 AM
Modern Data Architecture
Length: 45 Minutes
Description: This framework transforms data from disparate sources into a single dependable source of truth for all reporting and analytics.
An Enterprise Data Architecture Framework
One of the challenges facing enterprise architecture is maintaining consistency across the enterprise. This is challenging because data comes from disparate sources and systems representing different purposes, focuses, and objectives. On top of that, there needs to be more clarity regarding the terms “data lake,” “data warehouse,” “operational data store,” etc. To overcome these challenges at an enterprise level, a framework is necessary to apply data uniformly, consistently, and meaningfully.
Data Engineering
Length: 45 Minutes
Description: Strategic small-data systems can outperform large architectures when designed around the real problem, the real people, and the real business model.
Title: Simplicity as Strategy: Building Data Systems People Actually Trust
Time: 10:45 AM - 11:30 AM
Description: Today’s analytics environment is dominated by scale—more data, more layers, and more tooling. But in practice, many organizations are drowning in complexity rather than producing clarity. This session challenges the assumption that “bigger is better.” Drawing from experience across energy, finance, retail, and manufacturing, Meyer illustrates why overbuilt solutions become black boxes, slow response times, and weaken trust. He contrasts that with custom and constrained systems that are fast, interpretable, and resilient because they reflect how a business actually works.
Analytics & Semantic Layers
Length: 45 Minutes
Description: Gain actionable insights to accelerate your self-service analytics journey—enabling faster, more confident decision making and fostering a true culture of data-driven excellence.
Democratize Data via Semantic Layers & Self Service
Self-service analytics platforms are revolutionizing data accessibility and accelerating decision making across organizations. This session explores the strategic journey of building and scaling self-service analytics at Netflix Games, addressing the critical business need to democratize data. Attendees learn how semantic layers serve as the foundational bridge between complex data infrastructure and intuitive business analysis, enabling nontechnical users to generate insights independently—without needing to write SQL or understand database structures.
GenAI & Agentic AI
Length: 45 Minutes
Description: Accuracy and compliance become increasingly important with AI.
Stop Leaving It to Chance: How Adobe Ensures AI Gets the Facts Straight
As enterprises push AI deeper into mission-critical workflows, accuracy and compliance become nonnegotiable. A Model Context Protocol (MCP) connects AI models to verifiable external data sources in a way that AI understands. In this session, Adobe shares how its Taxonomy MCP and Content MCP now provide agents with governed, authoritative data, reducing risk while accelerating development. Our speakers cover the tools, patterns, and lessons learned, plus take a practical look at mapping taxonomy intents to LLM prompts to ensure consistent, verifiable outputs.
Data + AI Leadership Forum
Length: 45 Minutes
Description: Learn how to uncover and manage shadow AI, design governance that accelerates adoption, and build programs that balance innovation with accountability.
Title: There’s No AI Road Map Without a Data Road Map
Time: 10:45 AM - 11:30 AM
Description: This session challenges the common “AI-first” mindset and presents a practical, data-centric perspective on why AI success is fundamentally dependent on business alignment, data readiness, and operational governance. Attendees learn why AI is not software-driven but data-driven, how unclear data ownership and quality derail AI investments, and why AI systems require continuous iteration rather than one-time deployment. Drawing from enterprise and public-sector experience, the session introduces a structured approach that connects business intent to data readiness, model development, evaluation, and long-term operationalization.
11:45 AM
Modern Data Architecture
Length: 45 Minutes
Speaker(s):
Rajesh Vayyala, Principal Data Architect, Independent Research/Global Debt Recovery CompanyDescription: Get a pragmatic guide to choosing (and combining) 3NF, Data Vault, and Star schemas based on domain needs, not dogma.
From Source to Insight: 3NF, Data Vault, or Star—What Fits Your Domain?
This session maps each model to what it does best: 3NF for clean, conformed operational truth; Data Vault for auditable, change-tolerant ingestion with lineage; and Stars for fast, trustworthy analytics and semantic layers. Using an end-to-end example, we’ll show how a canonical domain model flows from bronze to silver (3NF/Vault) and into gold (Stars)—covering SCD-2, hierarchy versioning, snapshots vs. roll-forwards, and incremental CDC patterns. You’ll leave with a decision matrix and rollout recipes that balance governance, performance, and cost.
Data Engineering
Length: 45 Minutes
Description: AI is driving innovation across industries, but its growing energy demands pose critical challenges around cost, scalability, and sustainability.
Energy-Efficient AI: Building Sustainable Data Pipelines for the Future
This talk shares practical strategies for designing energy-efficient AI systems. It combines real-world case studies, industry frameworks, and research-driven practices to show how we can optimize AI pipelines for both performance and sustainability. Attendees leave with actionable approaches to measure, monitor, and minimize the carbon footprint of AI workloads, making sustainability a core design principle rather than an afterthought.
Analytics & Semantic Layers
Length: 45 Minutes
Description: This session discusses proven strategies for designing and operationalizing semantic layers across the organization.
GenAI & Agentic AI
Length: 45 Minutes
Description: By consolidating data that lives in multiple sources, companies can implement powerful AI personalization and prediction for actionable insights that improve customer interactions.
Title: Three Pillars, One Goal: The Data-AI-CX Transformation Framework
Time: 11:45 AM - 12:30 PM
Description: Customer experience is at a critical inflection point. With $3.8 trillion in sales at risk globally and over half of customers ready to walk away after a single poor interaction, the margin for error has disappeared. This session delivers a framework for transforming CX through data and AI integration. Learn the three-pillar approach that's helping organizations move from fragmented, reactive customer service to predictive, hyper-personalized experiences at scale. Attendees discover how to consolidate customer data from multiple sources into actionable insights, implement AI for personalization and prediction, and measure real ROI using the I-M-P-A-C-T methodology. Beyond technology, this session explores the organizational readiness factors—culture, team development, data governance, and metrics—that separate successful transformations from failed initiatives.
Data + AI Leadership Forum
Length: 45 Minutes
Speaker(s):
Vinnie Saini, Senior Gen AI/ML Specialist Solution Architect, Amazon Web Services Aditi Gupta, Senior AIML Specialist Solution Architect, Amazon Web ServicesDescription: Learn about real-world case studies demonstrating successful implementation of agentic AI solutions, best practices, and how to measure ROI.
Building With Purpose: Leveraging Agentic AI to Transform Enterprise Data Into Business Outcomes
In today's rapidly evolving technological landscape, organizations are sitting on vast amounts of untapped data potential. This session explores how agentic AI-driven systems are revolutionizing the way enterprises transform raw data into measurable business outcomes. Attendees leave well-informed with a solid understanding of the fundamental principles of agentic AI and its practical applications in enterprise settings and be ready to drive unparalleled business impacts.
2:00 PM
Modern Data Architecture
Length: 45 Minutes
Description: Discover how AI can supercharge data modeling through automated schema recommendations, pattern detection, and metadata generation.
Leverage AI to Transform Static Data Models Into Living Insights
This session delves into the indispensable role of data modeling throughout the AI lifecycle, from problem definition and data exploration to preparation, model training, deployment, and ongoing optimization. Attendees discover how AI can supercharge data modeling through automated schema recommendations, pattern detection, and metadata generation—without supplanting the irreplaceable value of domain expertise. It highlights emerging integrations, such as semantic technologies and Model Context Protocol servers, that transform static models into dynamic "living APIs" for enterprise intelligence across SQL, NoSQL, and cloud-native environments.
Data Engineering
Length: 45 Minutes
Description: AI-ready data is critical for successful initiatives.
Operationalizing AI-Ready Data: Why DataOps Automation Is Essential for Enterprise AI
AI initiatives continue to accelerate across the enterprise, yet many fail not because of model complexity, but because the underlying data is not ready. Organizations still battle inconsistent data quality, fragile pipelines, manual handoffs, and governance practices that cannot keep up with the pace of change required for AI. To succeed, enterprises must evolve from “good enough” data to AI-ready data: trustworthy, governed, observable, reproducible, and aligned to specific use cases.
Analytics & Semantic Layers
Length: 45 Minutes
Speaker(s):
Joe Pearce, Head of Product, RecordPointDescription: AI systems must be trained on trusted, relevant content to deliver true value.
Title: From ROT to ART: Why AI Needs Smarter Content, Not Just More
Time: 2:00 PM - 2:45 PM
Description: Organizations are drowning in “ROT” content (Redundant, Outdated, Trivial)—data that adds noise rather than value. When AI systems are trained on ROT, the outputs degrade: hallucinations, bias, and poor quality. In this session, attendees will learn how to shift from ROT to ART (Actionable, Relevant, Trusted) content that supports scalable, high-quality AI applications. You’ll walk through a proven framework for auditing existing content, identifying ROT, and remediating or enriching it with metadata, structure, and governance practices. The result? AI systems that are more accurate, defensible, and easier to maintain.
GenAI & Agentic AI
Length: 45 Minutes
Speaker(s):
Fleur Levitz, Principal Consultant, FDL Consulting NYC LLC, & former Data Governance executive on Wall StreetDescription: Vision-language models, including CLIP-like architectures, can transform raw images, video, and multimodal streams into structured, searchable, ML-ready datasets.
Title: Librarians in the Age of AI
Time: 2:00 PM - 2:45 PM
Description: Librarianship is redefining its role in the digital age, seamlessly bridging the gap between traditional KM practices and cutting-edge AI applications. Levitz examines several classical approaches to organize and rationalize human thought, namely through catalogs, classification schemes, and taxonomies. She highlights how librarians are stepping into pivotal roles within the AI-driven KM space—not just as knowledge managers but as ethical custodians. Their focus on transparency, inclusivity, and information integrity makes them indispensable partners in shaping responsible AI systems.
Data + AI Leadership Forum
Length: 45 Minutes
Speaker(s):
Dora Boussias, Executive Advisor & AI Leadership Keynote Speaker, DoraB GlobalDescription: This session examines the leadership patterns that shape whether AI strengthens credibility or quietly erodes it as adoption scales.
Leadership Trust in 2026: Executive Judgment When AI Is Everywhere
As AI becomes more embedded in everyday decision making, expectations rise, ambiguity increases, and decisions move faster. Trust becomes the make-or-break factor for adoption and impact, because leadership accountability does not disappear when AI enters the workflow. This session examines the leadership patterns that shape whether AI strengthens credibility or quietly erodes it as adoption scales. It offers leaders a clearer lens for what to watch for, what to question, and how to lead decisively without losing trust.
3:00 PM
Modern Data Architecture
Length: 45 Minutes
Description: Learn how Unity Catalog and Apache Iceberg can form an open lakehouse architecture that seamlessly works with multiple compute engines on Databricks.
Simplifying Data Interoperability With the Lakehouse Architecture on Databricks
Why did data lakes and warehouses pave the way for the Open Data Lakehouse? Modern platforms require flexibility, scalability, and governance for analytics and AI workloads. This session examines price/performance trade-offs between managed and foreign Iceberg tables and demonstrates how Databricks Unity Catalog enables unified governance with Apache Iceberg for open, efficient storage. Our speakers explore ACID-compliant transactional data and Change Data Capture for evolving datasets. A key highlight is cross-engine interoperability, integrating with AWS EMR, Redshift, and Athena, while remaining extensible to future engines.
Data Engineering
Length: 45 Minutes
Speaker(s):
Anil Inamdar, Global Head of Data Services, NetApp InstaclustrDescription: The open source data platforms already running your applications can power capable AI agents with targeted upgrades rather than wholesale replacement.
Your Open Source Data Infrastructure Is Ready for Agentic AI
Agentic AI looks new, but its infrastructure patterns aren’t. These are patterns Apache Kafka, Postgres with pgvector, Cassandra 5.0 with native vector indexing, and OpenSearch k-NN already handle. This session provides a composable blueprint for building agentic systems on your existing stack. Learn how Kafka lands events from apps and services in real time, how Postgres or Cassandra stores operational data and embeddings at scale, how OpenSearch indexes documents and vectors for fast retrieval, and how Kubernetes schedules agent services and model runtimes.
Analytics & Semantic Layers
Length: 45 Minutes
Speaker(s):
Erik Lee, Taxonomist / Information Architect, FactorDescription: This case study covers the lessons learned during a migration effort from a traditional RDBMS-based taxonomy management system to a graph-based environment.
Migrating From Hierarchies to a Graph: An Enterprise Case Study
A migration effort from a traditional RDBMS-based taxonomy management system to a graph-based environment opened the door for opportunities to consolidate existing vocabularies, eliminate duplicate concepts and attributes, and update the model into a richer semantic structure. Learn from experience of the work involved in such migrations, including the critical importance of preparation and testing, as well as considerations around modeling and potential disruptions to downstream consuming systems as a result of changes.
GenAI & Agentic AI
Length: 45 Minutes
Description: Explore the strategic, operational, and cultural implications of agentic AI and how to prepare for human and AI agents working side by side.
Agentic AI’s Impact to Operating Models
Agentic AI represents a profound shift in how organizations operate, and it is moving beyond automation to AI agents capable of taking on roles, not just tasks. This evolution is reshaping operating models, redefining governance and accountability, and transforming how humans and AI collaborate. This session explores the strategic, operational, and cultural implications of this transformation and outlines how leaders at every level can prepare for a future where human and AI agents work side by side.
Data + AI Leadership Forum
Length: 45 Minutes
Speaker(s):
Gaurav Goel, Head of Data Strategy & Transformation, Cardinal Health Ellen Brown, CEO, Slack ConsultingDescription: Set the foundation of an effective data-driven enterprise with clear accountabilities.
Title: The Data Domain Canvas
Time: 3:00 PM - 3:45 PM
Description: Dive into the depths of data domain discovery by leveraging a practical canvas designed to simplify this often-intimidating initiative. Become knowledgeable of which strategic questions you should be seeking answers to, and learn a methodical approach to the challenging discussions and activities required to set the foundation of an effective data-driven enterprise with clear accountabilities.
4:00 PM
Closing Keynote
Length: 1 Hour
Speaker(s):
John O'Brien, Principal Advisor & Industry Analyst, Radiant AdvisorsDescription: Despite unprecedented investment, most enterprise AI initiatives still struggle to deliver sustained business value. This keynote draws on our 2026 market research across 200-plus organizations to explain why—and what successful organizations are doing differently. We analyze how organizations are progressing from experimentation to measurable business impact and where initiatives most commonly stall. The session surfaces the key challenges limiting AI outcomes—including data readiness, platform complexity, organizational alignment, and trust—and examines the critical role of governance in enabling responsible, scalable AI. Drawing on evidence from across industries, we identify the architectural and operating patterns that consistently support AI success while balancing innovation with enterprise risk, compliance, and accountability.
