The State of Data Mesh
Watch the Great Data Debate to hear from data leaders who live, breathe, and weave data meshes and leave with practical insights into the world of the data mesh.
Hear from data visionaries,
thought leaders, and builders
Matthias has 25 years of experience in data management and serves as a trusted advisor to Snowflake clients and partners worldwide. He focuses on Enterprise Data Architecture, Data Collaboration, Data Governance, and related topics. He also leads the Data Mesh strategy at Snowflake.
Tristan Handy is the Founder and CEO of dbt Labs, an emerging leader in the data transformation space used by 25,000 companies including JetBlue, HubSpot, Dunelm, and Vodafone New Zealand.
Zhamak first defined the term "data mesh" in 2019 while she was working as a principal consultant at ThoughtWorks. Since then, the term has gained wide popularity as a paradigm shift toward data decentralization. She is also the author of the book "Data Mesh: Delivering Data-Driven Value at Scale.
Barr Moses is Co-Founder & CEO of Monte Carlo, a data reliability company and creator of the data observability category, backed by Accel, GGV, Redpoint, ICONIQ Growth, Salesforce Ventures, IVP, and other top Silicon Valley investors.
Teresa leads incubation and scaling of breakthrough technologies in cloud. She's the most prolific inventor at Accenture with 220+ patents and specializes in bridging the "enterprise gap" taking innovation from startups and academia to enterprise scale.
Scott is the CEO/founder of Data Mesh Understanding - a company dedicated to helping data mesh implementers get the info they need - and the host of Data Mesh Radio. He also co-founded the Data Mesh Learning community. He has interests outside of data mesh, he swears.
Abhi has been lucky enough to lead Growth and Data functions at high-growth and operationally excellent companies like Flexport, Honeybook, Keap, and Hustle. He is now "working on something new" at Levers Labs, building products and services to make every company a data-driven company.
On a quest to help the humans of data do more, together. Previously founded SocialCops, world leading data for good company (New York Times Global Visionary, World Economic Forum Tech Pioneer).
He works with customers on implementing modern data strategies, navigating key trends such as Data Mesh and Data Fabric. Austin spent the last 5 years as a Gartner Research Director.
The Data Mesh Toolkit: Is the Modern Data Stack All You Need?
Watch leaders of the modern data stack as they debate:
- The Data Mesh Toolkit: What are the essential pieces of software needed to implement a data mesh effectively?
- Beyond the Modern Data Stack: Is the modern data stack enough to implement a data mesh?
- No MDS, No Data Mesh?: Can data teams build an effective data mesh without the modern data stack?
Embracing Data Mesh: Cultivating the Right Mindset
Watch data mesh practitioners for a practical, interactive session on:
- Cultural Shifts: How to navigate the cultural changes necessary for a successful data mesh implementation.
- Collaboration and Empowerment: How data teams break down silos and empower team ownership of data domains.
- Success Stories & Business Impact: Stories of data mesh improving business outcomes, and how you can replicate their achievements.
Past events from the
great data debate
The AI-Led Data Stack
The founder of the Modern Data Stack. The mind behind the most widely-read data and AI report. The lead author of the Analytics and BI Magic Quadrant. The Head of Data & Analytics at Google Cloud.
All in one room. Debating the impact AI will have on the modern data stack… and data teams themselves. Who'd want to miss this?
Future of the Modern Data Stack
Watch the founders of the modern data stack for an interactive discussion on the changing data ecosystem and what lies ahead.
Future of Metrics Layer and Metadata
Metrics layers have been all the rage in 2022! We decided to bring the two of the most prolific product thinkers in this space to learn about their views on all things metrics layer and metadata.
Rebundling vs Unbundling of the Data Stack
This question has been everywhere – Reddit discussions, Twitter debates, community slack groups, data newsletters.