About Data Architecture Online

The annual Data Architecture Online event will cover key strategies and technologies you need to know in order to build and manage a modern Data Architecture. Tap into the combined expertise of several industry-leading professionals and connect with hundreds of data peers during this day of live, webinar-style sessions. Registration is free and gives you access to the sessions presented throughout the day, the live Q&A with the speakers, and all recorded presentations and materials.

The Schedule

2025 AGENDA

July 23, 2025 | 8 am Pacific

8:00

Trends in Data Architecture

Presented by John O’Brien

Moving beyond speculation to data. This keynote presents analysis and insights from our comprehensive Q1 2025 market study spanning 200+ organizations. We'll examine how companies are actually implementing modern enterprise data architectures to support analytics and AI initiatives, revealing current adoption rates, investment patterns, and expected outcomes. Building on our 2023 study's foundation, which tracked early investments in modern data architectures, we'll survey the evolution of data platforms by adding vector databases, knowledge graphs, and semantic layers. The session will cut through market hype to present evidence-based results and insights on which architectural patterns—from data fabric to data lakehouse—deliver measurable value and how organizations successfully balance AI innovation with enterprise data management and governance requirements.

9:00

Beyond the Algorithm: How Data Mastery Drives AI/ML Outcomes

Presented by Dave Wilkinson

As enterprises race to implement AI and machine learning, one truth remains: your models are only as good as the data feeding them. Without trusted, consistent, and well-mastered data, even the most sophisticated algorithms will struggle to deliver accurate, explainable, or actionable outcomes. This session explores how mastering your foundational data—through effective data governance, operational master data management, and purpose-driven architecture—can make your AI/ML strategy not only more complete but more impactful. We’ll share insights from real-world transformations, including how poor data hygiene reshaped financial reporting for a Fortune 500, how it took four months to answer a simple executive question, and how digital twins revolutionized predictive maintenance on oil platforms.

You’ll leave having experienced how to well-architect data ecosystems support scalable, trustworthy AI. We’ll dive into why operational efficiency begins with well-mastered data, how behavior change—not just dashboards—is the real measure of value, and why using generic AI models might erase your competitive edge. Whether you're leading a data team, evaluating ML platforms, or advancing enterprise architecture, this session will provide the frameworks, language, and real-world examples to bridge data mastery with artificial intelligence.

Attendees Will Learn:

  • Why MDM is foundational to trustworthy AI and ML outcomes
  • How to link master data, behavioral change, and operational efficiency
  • How to define and apply critical data elements based on real business purpose
  • Strategies for aligning MDM and analytics with measurable behavior change
  • How to support predictive analytics, digital twins, and advanced visualization through better architecture
  • Practical steps for architecting data environments that enable responsible, scalable AI adoption

10:00

Policy Meets Platform: Mapping Governance with Knowledge Graphs

Presented by Mark Horseman   In this session we'll show how knowledge graphs can be used to bridge the gap between enterprise policies (eg: Information Security, Document Management, Data Privacy, and External Data Sharing) and the actual data elements within a data lake. Linking specific fields to their governing policies, data owners, and usage contexts allows for the creation of a visual representation of data governance. This approach not only clarifies policy applicability but also reveals the centrality of key data assets. Implementation of a solution like this is surprisingly lightweight, requiring only a few steps to deliver a powerful solution.

11:00

Break

We will resume at 11:30am

11:30

KEYNOTE: Data Architecture for AI

As artificial intelligence continues to reshape industries, the foundation it stands on—data architecture—has never been more critical. This keynote panel brings together leading voices to explore how modern data architectures are evolving to meet the demands of AI-driven enterprises. Panelists will discuss the shift from traditional data warehouses to real-time, scalable, and decentralized frameworks; the role of data governance and quality in training reliable AI models; and how organizations can future-proof their infrastructure for emerging AI capabilities. Attendees will gain insights into best practices, common pitfalls, and forward-looking strategies to align their data architecture with the accelerating pace of AI.  

12:30

Session Title to Be Announced

Session abstract to be announced.

1:30

The Race For Data Quality in a Medallion Architecture

Presented by Christopher Berg

Would you like help maintaining high-quality data across every layer of your Medallion Architecture?

Like an Olympic athlete training for the gold, your data needs a continuous, iterative process to maintain peak performance. We will cover how Data Quality Testing, Observability, and Scorecards help you build accuracy, consistency, and trust at each layer—Bronze, Silver, and Gold. Discover how to make quality testing a built-in practice, empower your team to act fast, and ensure reliable insights from raw data to analysis-ready reports.

Whether you’re facing delayed data mismatches or need real-time quality assurance, we’ll give you practical tips and tools to keep your data flowing flawlessly.

What to Expect:

  • Winning Strategies for Each Medallion Layer: Discover how to tackle the unique data quality challenges of Bronze, Silver, and Gold layers in Medallion Architecture.
  • Get the DataOps Advantage: Learn how to apply DataOps to monitor, iterate, and automate quality checks—keeping data quality high without slowing down.
  • Practical Tools to Sprint Ahead: Dive into hands-on tips with open-source tools that supercharge data validation and observability.

Official DAO Sponsors

Interested in sponsoring DAO? Contact Francesca Djoufack by email: francesca@dataversity.net.

Become a Sponsor

FAQ

Here are a few good reasons why you should register:
  • Registration is free
  • There are six, 40-minute webinars
  • Learn from the best in the industry
  • Experience-based learning
  • Access to all recorded sessions, slides, and materials presented
  • Live Q&A following each webinar session
  • No, you do not need to pay anything to watch the live sessions presented during this event. When you register, we also give you free access to the on-demand recordings a couple of days after the event.
    It's OK if you can't attend the live event. Register and you will get access to the recordings of all the presentations and links to download the slides.
    Yes, we produce several face-to-face events around the country. DATAVERSITY is home to many educational events, online training options, webinars, white papers, articles, and blogs. We're proud to offer the worldwide data community so many educational opportunities both online and face-to-face. To learn more about what we do, visit dataversity.net.
    DATAVERSITY Education, LLC is an educational and publishing resource for business and Information Technology (IT) professionals on the uses and management of data. Our team strives to provide high-quality educational resources to our worldwide community of practitioners, experts, and developers who participate in and benefit from face-to-face hosted conferences, live webinars, white papers, online training, daily news, articles and blogs, and much more. Visit dataversity.net to learn more.

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