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



Trends in Data Architecture

Presented by Donna Burbank

With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this session to see the results of a recent DATAVERSITY survey on emerging trends in data architecture, along with practical commentary and advice from industry expert Donna Burbank.


Designing Data Governance for Data Mesh Architecture

Presented by Lauren Maffeo

Organizations own more data than ever before, but it’s of no value if you don’t know how to use it. Most organizations lack the strategy to clean, collect, organize, and automate data for production-ready projects.

The good news is that Data Governance – the people, processes, and strategy needed for deploying data projects to production – offers new opportunities to improve service delivery.

This session shares how leaders can embed Data Governance into data mesh cloud architecture. Attendees will learn how to unite cross-functional teams of data stewards to automate unified standards into data mesh, which emphasizes data domain ownership through self-service architecture.

Whether you’re a chief data officer or individual contributor, this talk will show you how to manage up, get the buy-in you need to build Data Governance, find the right colleagues to co-create governance, and build cloud architecture that better serves the public.


The Importance of Strategically Positioning MDM in Today’s Architecture

Presented by Frank Cerwin

Master data has been present in organizations’ systems since the first application was deployed decades ago. As applications multiplied, trading partner relationships grew, government regulations were imposed, and mergers and acquisitions occurred, managing master data became extremely challenging and issues proliferated. Today’s organizations have launched or are planning numerous strategic business initiatives that depend on their master data to be accurate, shareable, protected, and fit for purpose where applied. Unfortunately, many organizations continue to struggle with an effective master data management (MDM) program. To meet these challenges requires defining and positioning the MDM program strategically in the system architecture and organizational structure.

Covered topics include:
  • MDM’s importance to the success of digital transformation, government regulation compliance, Internet of Things (IoT), and M&A migration
  • Taking a holistic perspective to MDM program positioning
  • The impact of an organization’s structure, culture, and industry on an MDM program



We will resume at 11:30am


KEYNOTE: Fad or Fundamental? New Possibilities for Your Data Architecture

Presented by Donna Burbank, Juan Sequeda, Lauren Maffeo

ChatGPT: Is it just hype? Something only to be used by students to write their papers? Or are there practical applications for it within your Data Architecture? What about other emerging technologies? What should you be paying attention to?

In this keynote, Donna Burbank, principal speaker of the monthly DATAVERSITY webinar series Data Architecture Strategies, will facilitate an expert panel discussion to determine Fad or Fundamental.


Case Study: Data Mesh – Federated Query and Access Control Over Data Products

Presented by Barbara Eckman

As Zhamak Dehghani defines it in her seminal book “Data Mesh: Delivering Data-Driven Value at Scale,” data mesh is based on four core principles:

  • Decentralized domain ownership
  • Data as a product
  • Self-serve data platform
  • Federated computational governance

She writes, “The data products created by each domain team should be discoverable, addressable, trustworthy, possess self-describing semantics and syntax, be interoperable, secure, and governed by global standards and access controls.” These principles ensure an improved level of reliability and ease of use for consumers, while still maintaining high data protection standards.

In this talk, I will outline an approach to building an enterprise data mesh to honor these principles. Our data mesh spans a wide variety of data products, including on-prem and public cloud and SQL, noSQL, and API-only access. We support federated queries across these data products using Presto/Trino and Spark SQL. Fine-grained role-, tag-, and attribute-based access control are provided using extensions of Apache Atlas and Ranger, fully automated after an initial metadata specification. Self-service discovery and access control are provided on a column/attribute level.

Our data mesh vision is not yet fully realized. I’ll share the progress we’ve made toward this vision and the lessons we’ve learned along the way.


Data Architecture for Machine Learning

Presented by Dave Wells

Machine learning is at the cutting edge of modern data use cases. After years of slow and painstaking advances, machine learning is experiencing rapid adoption today. Machine learning uses statistical methods to make predictions and to automatically improve prediction accuracy over time. In business it is readily applied to common analytics problems such as quantitative investing, customer recommendations, medical diagnosis, predictive maintenance, fraud prevention, and more. And today’s hottest technologies – generative AI – are built on a machine learning foundation. We are in the early stages of a steep adoption curve for machine learning.

To prepare for machine learning, it is important to focus on Data Architecture. You don’t need (and don’t want) a separate Data Architecture for machine learning. Instead, think about how to extend your existing Data Architecture. What new Data Management capabilities do you need? What new architectural features and functions should be intergrated into your Data Architecture?

A Google data scientist once said that simple models working with very large datasets are more accurate than complex models with small amounts of data. So, data volume is certainly a consideration, but it is only the beginning. Join this session to learn about these Data Architecture considerations for machine learning:

  • Data Architecture for massive data volumes
  • Real-time data pipelines
  • A single database for transactions and analytics
  • Redeploying batch models in real time
  • Data preparation for supervised learning
  • Data preparation for unsupervised learning
  • Write-back Data Management (machine learning creates new data)

Official 2023 DAO Sponsors

Interested in sponsoring DAO? Contact Warwick Davies by email: warwick@dataversity.net or phone: 1-781-354-0119.

Become a Sponsor


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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