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 preserve trust and deliver value at scale.
9:30 AM
Keynotes
Length: 15 Minutes
Description: As AI agents take on more responsibility in your enterprise, many teams are confronting a hard truth: AI is only as reliable as the data behind it. In large organizations, data is typically distributed, inconsistently governed, and difficult to interpret, making it risky for AI agents to operate with confidence. Gabriel looks at what it truly means to make your data ready for AI agents, beyond simple access or scale. He explores how context, lineage, and governance help agents discover, understand, and safely use enterprise data. Discover a practical approach to building data foundations your AI agents can rely on for trustworthy, auditable outcomes.
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.
Title: Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, & Data Mesh
Time: 10:45 AM - 11:45 AM
Description: 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.
Title: Composable, Scalable Data Pipeline Frameworks
Time: 10:45 AM - 11:45 AM
Description: This session explores the transition to language-agnostic authoring, multi-tenancy, and microservices and discusses 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: Architecting for AI cohesively and at scale requires intentionally designing a connected knowledge, data, and AI ecosystem.
Title: How to Implement Semantic Layer Architectures that Enable Enterprise AI
Time: 10:45 AM - 11:45 AM
Description: This session will present the emerging trends within the enterprise data ecosystems and discuss case studies that take a deep dive into Semantic Layer technical architectures, exploring the components that enable enterprise-scale data transformation efforts leveraging semantic capabilities, such as federated metadata management, ontologies, and knowledge graphs. The presentation will explore the top four architectural patterns that have been successfully implemented at multiple organizations, highlighting the best practices for enabling enterprise AI.
Title: Same Question, Same Answer: How Agents Build Your Data Context Graph in Days
Time: 10:45 AM - 11:45 AM
Description: Building ontologies, knowledge graphs, and semantic layers still takes months of data engineering effort. See how data engineering agents autonomously construct and maintain a data context graph that delivers deterministic analytics using neuro-symbolic models, where the same question always produces the same SQL and the same answer. Also learn how these agents help data platform leaders with ingestion, transformation, data quality, and governance.
GenAI & Agentic AI
Length: 1 Hour
Speaker(s):
Mou Rakshit, Databricks Champion Solution Architect, Accenture / Avanade Michael Rounds, Product Evangelist, WisdomAIDescription: 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.
Title: From Data Chaos to Trusted AI: Building Context and Governance for Agentic Analytics Abstract
Time: 10:45 AM - 11:45 AM
Description: Organizations have spent the last 20 years building systems to manage data—but almost no time building systems to manage context. Yet context is what ultimately determines whether an AI-generated answer is right or wrong—and it’s constantly evolving. As enterprises adopt agentic analytics, this gap is becoming impossible to ignore. AI agents can reason across vast amounts of data, but without the right context, their outputs risk being incomplete, inconsistent, or untrustworthy. Layering AI on top of an already complex data stack raises new challenges around governance, control, and accountability.
Data + AI Leadership Forum
Length: 1 Hour
Speaker(s):
Asaf Bord, GenAI Product Leader, Asaf Bord Chip Schenck, Principal, Generative AI & Data Strategy, IBMDescription: Learn what key AI transformations mean for data teams, architecture teams, product strategy, governance, and investment planning—and how to prepare today.
Title: Five Transformations Reshaping Enterprise GenAI: What Leaders Should Prepare For
Time: 10:45 AM - 11:45 AM
Description: 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.
Title: Stop Asking If Your Data Is Ready. Start Asking If You Are.
Time: 10:45 AM - 11:45 AM
Description: For years, the conversation around AI has centered on data readiness—cleaning it, governing it, making it accessible. But the organizations making the most progress have quietly shifted the question. Not “Is our data ready?” but “Are we ready to make the decisions that matter?” Decision readiness reframes the entire data and AI conversation for senior leaders. It connects data investments to business outcomes in language understood by every seat at the table. It makes governance feel strategic rather than bureaucratic. And it gives leadership teams a shared lens for prioritizing where to act first. This session introduces the decision readiness frame and shows how leadership teams across industries are using it to cut through complexity and start delivering value.
12:00 PM
Modern Data Architecture
Length: 45 Minutes
Description: This session features a case study covering the data platform that provides the scientific data backbone as part of a unified data architecture.
Title: A Use Case for a Hybrid Data Mesh Architecture
Time: 12:00 PM - 12:45 PM
Description: 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.
Title: Agentic MDM, Simplified: A Monotype Story
Time: 12:00 PM - 12:45 PM
Description: How can you simplify agentic MDM adoption without a lengthy implementation? Monotype integrated multiple CRMs and enterprise systems using Syncari's agentic MDM platform, autonomously cleansing and syncing data. Its "start small, prove the model" approach delivered faster AI-driven insights, improved data quality, and reduced infrastructure costs.
Data Engineering
Length: 45 Minutes
Description: Learn how data engineering teams can unify structured, semi-structured, and unstructured data for multimodal AI training.
Title: From Data Lake to AI Lakehouse: Engineering Foundations for GenAI
Time: 12:00 PM - 12:45 PM
Description: 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.
Title: Learning From Failure: Building a Data & AI Governance Framework Through Real-World Case Studies
Time: 12:00 PM - 12:45 PM
Description: 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.
Title: From Chaos to Clarity: A Multi-Agent Architecture for Intelligent Digital Commerce Catalogs
Time: 12:00 PM - 12:45 PM
Description: 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.
Title: Building the Agentic AI Future with Databases
Time: 12:00 PM - 12:45 PM
Description: Explore how Google Cloud Databases accelerate development and reduce operational overhead with near-instant provisioning and an AI-native toolchain, including managed Model Context Protocol (MCP) servers. Learn how AI agents integrate seamlessly with managed databases to simplify the end-to-end lifecycle from development through production and ongoing maintenance.
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.
Title: Learnings From the Front Lines of AI
Time: 12:00 PM - 12:45 PM
Description: 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.
Title: The Agent That Retrieves Best, Wins
Time: 12:00 PM - 12:45 PM
Description: Enterprise AI agents are only as intelligent as what they retrieve—yet most organizations are investing heavily in models while ignoring the layer that determines whether those models reason accurately, act on current knowledge, and deliver distinctive results. This session reveals why retrieval is the decisive competitive variable in agentic AI, exposes the organizational and architectural gaps most teams don’t know they have, and gives every attendee a concrete framework to assess where they stand — and what to do Monday morning.
2:00 PM
Modern Data Architecture
Length: 45 Minutes
Description: Learn how GenAI can augment and enhance data inside enterprise data warehouses securely, at scale, and with measurable value.
Title: A Blueprint for Enterprise Data Warehouses
Time: 2:00 PM - 2:45 PM
Description: 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):
Hina Gandhi, Software Engineering Technical Leader, CiscoDescription: Tips and techniques to pave the way for autonomous, efficient data pipelines that continuously adapt to changing workloads and infrastructure dynamics.
Title: Teaching Spark to Tune Itself: Reinforcement Learning for Smarter Optimization
Time: 2:00 PM - 2:45 PM
Description: This talk introduces an approach that empowers Spark to learn how to optimize itself—using reinforcement learning (RL), specifically Q-learning, to dynamically choose the most efficient partition strategies at runtime. We explore how an RL agent can observe key performance signals—such as shuffle size, task duration, data skew, and executor utilization—and iteratively refine its partitioning decisions to minimize latency and resource cost. Attendees hear insights into designing the RL environment, defining meaningful reward functions, and integrating agents with Spark’s existing AQE.
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.
Title: From Data Warehouses to Organization-Wide GenAI Access
Time: 2:00 PM - 2:45 PM
Description: 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.
Title: Framework for Production-Grade AI Agents
Time: 2:00 PM - 2:45 PM
Description: 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.
Title: Agentic Architecture in Production: Fast Context Retrieval With ClickHouse
Time: 2:00 PM - 2:45 PM
Description: AI agents are only as good as the data they can access. In production, speed and scale matter. Steinkamp explores how ClickHouse serves as the real-time data layer for production AI agents, enabling fast context retrieval, low-latency decisioning, and scalable memory across complex agentic workflows. She walks through real-world agentic architectures from the ClickHouse community, covering how teams handle high-cardinality datasets, embedding stores, and retrieval pipelines at scale. Attendees leave with practical guidance on designing agentic systems that remain fast and reliable in production and where ClickHouse fits into the stack.
Data + AI Leadership Forum
Length: 45 Minutes
Description: Get actionable frameworks and questions to ask to accelerate the responsible deployment of GenAI and agentic AI.
Title: From Pilot to Production: The Executive Playbook for Scaling GenAI & Agentic AI
Time: 2:00 PM - 2:45 PM
Description: 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.
Title: See AI in Action: Building Trusted Data Products With Quest
Time: 2:00 PM - 2:45 PM
Description: Preparing data for analytics and AI often takes months—slowed by manual processes, unclear requirements, and governance gaps. Data products promise high returns, but without standards and structure, each line of business will create its own idea of what a data product is and skip important data management practices. In this session, experience how Quest is using GenAI to redefine the data control plane by automating the creation of trusted data products without sacrificing speed and trust. See a live walkthrough of how AI interprets a data request and generates a logically defined “Data Product Spec” that includes the associated business context, physical data locations, governance controls, and a measurable trust score. Learn how this approach enables faster delivery, higher confidence, and AI-ready data from Day One.
3:15 PM
Modern Data Architecture
Length: 45 Minutes
Description: How to structure data flow for reuse, governance, and agility.
Title: Revolutionizing Data Value Chains: Medallion Architecture Meets Microsoft Fabric
Time: 3:15 PM - 4:00 PM
Description: The Medallion Architecture—organizing data into bronze (raw), silver (cleansed), and gold (curated) layers—has become a proven framework for scalable data transformation and analytics. This session explores how Microsoft Fabric elevates the Medallion Architecture into a unified, enterprise-grade data ecosystem. By integrating OneLake, Direct Lake, Synapse Data Engineering, Power BI, and AI-powered governance into a single SaaS platform, Fabric enables frictionless transitions between raw ingestion, transformation, and insight delivery.
Title: Five Steps to Achieve Data Sovereignty
Time: 3:15 PM - 4:00 PM
Description: In an AI-first world, data sovereignty isn't a nice-to-have. Cybersecurity, regulatory, and data governance challenges make it a must-have. Join this session to learn five steps that you can take to achieve data sovereignty.
Data Engineering
Length: 45 Minutes
Speaker(s):
Ian Phillips, Chief Data Architect, Lockheed MartinDescription: Protecting valuable data requires ensuring data security across the entire lifecycle of the data.
Title: Information Lifecycle Thinking: Documenting Digital Threads
Time: 3:15 PM - 4:00 PM
Description: Protecting valuable data requires systems that proactively manage data across its complete lifecycle, as it is copied or moved from custodian to custodian. To enable ongoing protection, receiving custodians need to know what data protection is required, and custodians must agree to protect the data the same way that the original data owner would want to have it protected. This presentation discusses the prospect for data security federation, an approach that enables the appropriate level of data security across the entire lifecycle of the data.
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.
Title: The Missing Layer: How Semantics & Metadata Connect People, Data, & AI
Time: 3:15 PM - 4:00 PM
Description: 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.
Title: Responsible AI & Privacy: Trusted Data for Analytics at Speed
Time: 3:15 PM - 4:00 PM
Description: Okezie 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. He 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.
Title: Trusted Data for Analytics at Speed
Time: 3:15 PM - 4:00 PM
Description: Luthra shows how teams deliver compliant, high-quality data wherever it’s needed across AI and analytics initiatives, including modern platforms like Snowflake, Databricks, and Azure/Fabric.
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.
Title: Data Mesh as the Foundation for AI/ML in Financial Services
Time: 4:15 PM - 5:00 PM
Description: 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 practical strategies for building fail-safe data platforms by embedding proactive validation, continuous monitoring, and resilient architectural patterns.
Title: From Fragile to Fail-Safe: Designing Robust Data Platforms
Time: 4:15 PM - 5:00 PM
Description: 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: The models for analysis sharpen your focus on the missing data in any and all problems.
Title: Formulas for Aha
Time: 4:15 PM - 5:00 PM
Description: 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.
Title: Empowering Healthcare Transformation: Harnessing GenAI for Data Intelligence & Scalable Innovation
Time: 4:15 PM - 5:00 PM
Description: 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.
Title: AI Risks & Risk Mitigation Strategies
Time: 4:15 PM - 5:00 PM
Description: 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.
