8:45 AM
Keynotes
Length: 45 Minutes
Description: Executives are betting on agentic AI to drive growth, yet many enterprises still struggle to move from pilot to production. The hard part has never been the models. It is about building trust in underlying data assets, human-AI workflows, and outcome accountability. Enter Trust Engineering, the emerging discipline you need to consistently scale AI beyond pilots. It brings together the trust infrastructure required to support agentic AI in production, design patterns that improve human-AI decision making in operational workflows, and best practices for creating a culture of accountability around AI-driven outcomes. Through real-world case studies and examples, attendees will receive a practical framework for building and deploying agentic systems that preserves trust and delivers value at scale.
10:45 AM
Modern Data Architecture
Length: 1 Hour
Speaker(s):
James Serra, Data & AI Architect, MicrosoftDescription: Learn the pros and cons of data fabric, data lakehouse, and data mesh as alternatives to the modern data warehouse.
Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, & Data Mesh
Data fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. This presentation provides a guided tour of each architecture to examine common data architecture concepts. Learn what data lakehouses can help you achieve, how to distinguish data mesh hype from reality, and how to determine the most appropriate data architecture for your needs. The session finishes by discussing Microsoft’s version of the data mesh.
Data Engineering
Length: 1 Hour
Description: This session looks at a composable, scalable data pipeline framework to support large production workloads.
Composable, Scalable Data Pipeline Frameworks
This session explores the transition to language-agnostic authoring, multi-tenancy, and microservices and discuss automated migration and validation strategies. Attendees see architecture diagrams, platform comparisons, and quantifiable results from production deployments, including reliability and performance wins. Hear lessons learned, failures, and successes and gain actionable frameworks for building product-centric data platforms that accelerate value delivery.
Analytics & Semantic Layers
Length: 1 Hour
Description: Expect a grounded walkthrough of the architecture, governance model, and cultural changes behind making marketing data truly interoperable.
Building Uber’s Marketing Semantic Layer
Uber is connecting the dots between fragmented datasets by building a marketing semantic layer: a shared data foundation that stitches together marketing concepts, metrics, and identifiers across sources to create a single, queryable source of truth. This session unpacks the design of the semantic layer and its companion “context registry,” which captures the evolving business meaning behind metrics and entities. Attendees learn how this system helps analysts, scientists, and marketers interpret performance shifts faster, automate root cause analysis, and reduce time spent reconciling inconsistent data definitions.
GenAI & Agentic AI
Length: 1 Hour
Speaker(s):
Mou Rakshit, Databricks Champion Solution Architect, AccentureDescription: Learn how to design a closed loop “sense, reason, act” pattern on Microsoft Fabric Real-Time Intelligence.
Title: From Signal to Action in Microsoft Fabric RTI: Data Agents, Digital Twins, Activator, & Copilot
Time: 10:45 AM - 11:45 AM
Description: Dashboards don’t fix incidents—actions do. This session shows how to design a closed-loop “sense, reason, act” pattern on Microsoft Fabric Real-Time Intelligence, where data agents turn raw telemetry into safe, auditable remediation. Events will be streamed via Eventstream into Eventhouse (KQL) to detect anomalies and trigger Activator reflexes that launch agent plans. The agents consult a digital twin to and business context and leverage Copilot Studio to carry out changes in tools that lack APIs—under human approvals, guardrails, and OneLake governance.
Data + AI Leadership Forum
Length: 1 Hour
Speaker(s):
Asaf Bord, GenAI Product Leader, Asaf BordDescription: Learn what key AI transformations mean for data teams, architecture teams, product strategy, governance, and investment planning—and how to prepare today.
Five Transformations Reshaping Enterprise GenAI: What Leaders Should Prepare For
GenAI is evolving faster than most enterprises can adapt. What matters now is not chasing individual tools or models but understanding the structural trends that will define how AI is built, deployed, governed, and valued. This talk outlines the five transformations that will reshape enterprise AI architectures and operating models over the next 3–5 years. Each trend is grounded in real enterprise experience, market analysis, and architectural patterns emerging across the industry.
12:00 PM
Modern Data Architecture
Length: 45 Minutes
Speaker(s):
Norman Adkins, Deputy Director, U.S. Environmental Protection AgencyDescription: This session features a case study covering the data platform that provides the scientific data backbone as part a unified data architecture.
A Use Case for a Hybrid Data Mesh Architecture
The computational toxicology (CompTox) data platform provides the scientific data backbone for the EPA. It integrates data modeling, engineering curation, and cloud-based processing to deliver high-quality, reproducible pipelines and datasets that support EPA research, regulatory decision making, and public-facing tools. The platform serves as a unified, enterprise-grade environment that enables efficient data processing, consistent data standards, and scalable infrastructure to support the agency's mission in computational toxicology and exposure science.
Data Engineering
Length: 45 Minutes
Description: Learn how data engineering teams can unify structured, semi-structured, and unstructured data for multimodal AI training.
From Data Lake to AI Lakehouse: Engineering Foundations for GenAIa
GenAI relies not only on powerful models but also on the quality and accessibility of enterprise data. This session dives into how data engineering teams can evolve their lakes into “AI lakehouses”—unifying structured, semi-structured, and unstructured data for multimodal AI training. Explore storage formats (Delta, Iceberg), scalable ETL/ELT pipelines, and vector databases for retrieval-augmented generation. Through practical patterns, see how teams can ensure data quality, reduce duplication, and power new AI use cases.
Analytics & Semantic Layers
Length: 45 Minutes
Description: Uncover the patterns behind governance breakdowns and translate them into a practical framework.
Learning From Failure: Building a Data & AI Governance Framework Through Real-World Case Studies
AI is reshaping industries, but without strong governance, it can lead to biased decisions, unreliable outputs, and harmful misuse of data. These failures are rarely just technical; they reveal deeper gaps in how organizations manage risk, accountability, and trust. This session shows how enterprises can shift from reactive compliance to proactive safeguards that strengthen reliability, transparency, and business value. Learn actionable principles for embedding governance as a foundation for responsible AI adoption and sustainable innovation.
GenAI & Agentic AI
Length: 45 Minutes
Description: During this session, attendees explore a practical blueprint for building intelligent, self-correcting digital commerce catalogs at global scale.
From Chaos to Clarity: A Multi-Agent Architecture for Intelligent Digital Commerce Catalogs
Digital commerce platforms struggle to keep product catalogs consistent, compliant, and up-to-date as they expand across regions, channels, and business models. Legacy catalog processes remain fragmented and sequential, relying on manual handoffs between pricing, merchandising, payments, and policy teams, while brittle automation fails on exceptions, incomplete data, and nuanced regulatory constraints. This session presents a multi-agent architecture that transforms catalog creation and evolution into an intelligent, federated workflow spanning heterogeneous services and AI agents.
Data + AI Leadership Forum
Length: 45 Minutes
Description: Get a candid look at lessons every leader needs to understand to make AI a competitive advantage.
Learnings From the Front Lines of AI
This candid and practical session separates the signal from the noise, exploring what’s truly working in AI implementations across industries and where companies are falling short. From the common pitfalls that derail well-intentioned efforts to the design principles behind AI initiatives that create measurable value, Frederick shares the lessons that every leader needs to understand to make AI a competitive advantage rather than a costly experiment.
2:00 PM
Modern Data Architecture
Length: 45 Minutes
Speaker(s):
Coleman Hilton, Director of Data Engineering and Analytics, Shriners Children'sDescription: Learn how GenAI can augment and enhance data inside enterprise data warehouses securely, at scale, and with measurable value.
A Blueprint for Enterprise Data Warehouses
Drawing from real-world work attribution projects in clinical documentation, we explore how OpenAI models were used to generate structured, high-fidelity metadata from free-text notes, dramatically improving attribution accuracy and downstream reporting. Attendees learn a generalizable pattern for applying GenAI to any domain: selecting augmentation targets, creating controlled pipelines, validating model outputs, and integrating AI-derived fields into production semantic models. The talk provides a practical, architecture-ready framework to elevate data quality, accelerate analytics, and unlock new enterprise intelligence.
Data Engineering
Length: 45 Minutes
Speaker(s):
Bhavya Tyagi, Senior Software Engineer, LinkedInDescription: Explore how introducing governance, infrastructure as code (IaC), and dynamic controls into logging pipelines help address complexity, chaos, and costs.
Taming Log Chaos: Optimizing & Scaling Observability With IaC & Dynamic Controls
Logs are the lifeblood of observability, but at scale, they often turn into uncontrolled chaos, driving up costs, complexity, and operational pain. This session shares practical approaches for standardizing log ingestion, automating controls with peer-reviewed IaC, and dynamically tuning configurations and routing to balance reliability with cost efficiency. Hear lessons based on real-world experience on reducing noise, scaling logging platforms sustainably, and empowering developers with streamlined workflows. Learn actionable strategies to optimize observability, cut waste, and regain control over logs.
Analytics & Semantic Layers
Length: 45 Minutes
Description: Semantic models allow GenAI systems to reason over enterprise data by encoding business meaning and structure, yet they are often limited by adoption risks as data and AI usage scale.
From Data Warehouses to Organization-Wide GenAI Access
This talk introduces a schema-aware semantic model management framework that democratizes semantic models across the organization. By automating schema change detection, maintaining versioned model history, and exposing a centralized, governed repository, semantic models become a shared asset consumable by diverse stakeholders—including analysts, product managers, and AI agents who do not have direct access to the data warehouse. The result is broader access, safer AI reasoning, and true self-service intelligence at scale.
GenAI & Agentic AI
Length: 45 Minutes
Description: Learn practical strategies to apply engineering rigor to AI agent development, transforming proofs-of-concept into scalable enterprise applications.
Framework for Production-Grade AI Agents
This session outlines a comprehensive framework for production-grade AI agents that are designed to bridge the significant gap between clever AI demos and dependable, reliable systems used in production environments. The framework emphasizes that building successful agents requires a new engineering discipline, focusing on intelligent architecture over simply using the largest available model. The session introduces the five Pillars of Agentic AI Engineering to apply engineering rigor to AI agent development, transforming creative proofs-of-concept into scalable, trustworthy enterprise applications.
Data + AI Leadership Forum
Length: 45 Minutes
Speaker(s):
Travis Jones, Chief Operating Officer & AI Transformation Leader, Logic20/20Description: Get actionable frameworks and questions to ask to accelerate the responsible deployment of GenAI and agentic AI.
From Pilot to Production: The Executive Playbook for Scaling GenAI & Agentic AI
GenAI and agentic AI are accelerating fast, but many enterprises still struggle to navigate to real-world production systems that are reliable, governable, and aligned with business objectives. This discussion is designed for technical and business leaders who want proven patterns for scaling their AI initiatives. Understand what “production-ready” means for AI systems, how to incorporate GenAI and agentic AI into enterprise workflows seamlessly, how to handle shadow AI, and a pragmatic set of KPIs that help leaders scale what works and stop what doesn’t.
3:15 PM
Modern Data Architecture
Length: 45 Minutes
Description: This session presents a blueprint for building a large-scale data lakehouse on the Microsoft Azure platform.
Data Engineering
Length: 45 Minutes
Description: Check back for details.
Analytics & Semantic Layers
Length: 45 Minutes
Description: This talk frames semantics as the connective tissue that allows people and AI to work from the same understanding of data.
The Missing Layer: How Semantics & Metadata Connect People, Data, & AI
Modern data ecosystems are rich in tools but poor in shared understanding. Metadata is scattered across catalogs, observability platforms, governance systems, and tribal knowledge, while people and AI systems are expected to collaborate on top of this fragmentation. This session examines why metadata and semantics must evolve together to support both human decision making and AI automation. The real challenge is not tooling, but the absence of a unified layer that captures meaning, context, and accountability across the data lifecycle.
GenAI & Agentic AI
Length: 45 Minutes
Description: Explore evidence-based practices that enable organizations to implement AI systems while safeguarding stakeholder privacy and maintaining trust.
Responsible AI & Privacy
The presentation covers the critical intersection of responsible artificial intelligence (RAI) and privacy protection in organizational contexts. It is derived from research on AI governance mechanisms and the prevention of privacy violations. The presentation explores evidence-based and actionable practices that enable organizations to implement AI systems while safeguarding stakeholder privacy and maintaining trust, along with practical solutions to address costly privacy violations, helping managers navigate responsible AI adoption with greater confidence.
Data + AI Leadership Forum
Length: 45 Minutes
Description: It’s not just about technology; Successful AI adoption requires strong, visionary leadership. This panel of thought leaders will share insights and guidance on how to translate strategy into desired business outcomes in a rapidly changing, uncertain landscape.
4:15 PM
Modern Data Architecture
Length: 45 Minutes
Speaker(s):
Santosh Durgam, Manager of Software Engineering, Morningstar Investments Inc.Description: Hear how a data mesh becomes the foundation for reliable, reusable AI/ML features and trustworthy models.
Data Mesh as the Foundation for AI/ML in Financial Services
Financial institutions want AI/ML at scale, but brittle data pipelines, silos, and compliance demand slow progress. This talk shows how a data mesh—domain-oriented ownership, data-as-product, self-serve platforms, and federated governance—becomes the foundation for reliable, reusable ML features and trustworthy models. Attendees get a pragmatic blueprint: where to start, how to sequence capabilities, metrics that prove value, and pitfalls to avoid on the road from pilots to production.
Data Engineering
Length: 45 Minutes
Description: Learn how practical strategies for building fail-safe data platforms by embedding proactive validation, continuous monitoring, and resilient architectural patterns.
From Fragile to Fail-Safe: Designing Robust Data Platforms
Modern data platforms are the backbone of enterprise decision making, yet many pipelines remain fragile and susceptible to silent failures, data drift, and operational bottlenecks. Through real-world enterprise examples, this session highlights how organizations can shift from reactive firefighting to proactive reliability, reducing downtime, improving MTTR, and instilling confidence in data platforms. Participants gain actionable insights and design patterns to engineer data platforms that are predictable, resilient, and trusted, enabling reliable analytics and decision making across complex, distributed environments.
Analytics & Semantic Layers
Length: 45 Minutes
Description: New models in analysis will sharpen your focus on the missing data in any and all problems.
Formulas for Aha
Are you tired of waiting for an "aha" moment in your analysis? Look no further. As a life-long data scientist and mathematician, Wilson Chase dives into pattern recognition that allows her to create formulas for seemingly spontaneous moments of brilliance—of aha. She is the creator of two new models in analysis that will sharpen your focus on the missing data in any and all problems.
GenAI & Agentic AI
Length: 45 Minutes
Description: GenAI provides powerful new methods for data synthesis, automation, and insight generation.
Empowering Healthcare Transformation: Harnessing GenAI for Data Intelligence & Scalable Innovation
This session explores practical strategies for integrating LLMs and multimodal systems into healthcare analytics and enterprise architectures. Drawing from real-world implementation experience, the talk highlights how organizations can leverage GenAI to streamline data workflows, enhance predictive accuracy, and enable personalized care—while maintaining privacy, compliance, and human oversight. Attendees gain a comprehensive understanding of both the architectural and ethical dimensions of GenAI, with actionable guidance on designing scalable, trustworthy, and human-centered AI ecosystems that drive measurable business and clinical outcomes.
Data + AI Leadership Forum
Length: 45 Minutes
Description: Recognize 10 critical AI risks, detect emerging issues early, and implement practical measures to mitigate them.
AI Risks & Risk Mitigation Strategies
As organizations embrace AI technologies, they face growing challenges related to fairness, privacy, and unpredictable system behavior. This session uses real-world examples to help attendees recognize 10 critical AI risks, detect emerging issues early, and implement practical measures to mitigate them while maximizing business value. The discussion also emphasizes the role of AI governance as a foundation for responsible and sustainable AI adoption.
5:00 PM
Networking Reception in the Data + AI Showcase
Length: 1 Hour
Description: Join us during drinks, light bites and networking in the showcase! Featuring leading industry vendors, the Data + AI Solutions Showcase offers a vibrant marketplace to explore cutting-edge solutions in data management, data architecture and engineering, analytics, and AI. Whether you have a specific project that needs help or you just want to keep up with the latest tools, strategies, and trends, the showcase is a can't miss destination.
