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Data Mesh Resource Center
Data Mesh is a decentralized, distributed approach to optimize enterprise data management and help organizations get the most out of their data-driven investments
Enjoy exclusive access to Data Mesh content, including on-demand talks, panel discussions featuring Zhamak Dehghani, Founder of Data Mesh, and more!
What is Data Mesh?
Data Mesh – an approach founded by Zhamak Dehghani – refers to a decentralized, distributed approach to enterprise data management. It is a holistic concept that sees different datasets as distributed products, orientated around domains. The idea is that each domain-specific dataset has its own embedded engineers and product owners to manage that data and its availability to other teams, driving a level of data ownership and responsibility, which is often lacking in the current data platforms that are largely centralized, monolithic, and often built around complex pipelines.
Data Mesh is founded around four core principles:
Defining Data Mesh
In this video, Adrian Estala, VP, Field CDO, gives a high-level introduction to the fundamentals of Data Mesh.
How to Integrate Data Mesh Into Your Ecosystem
In this video, Adrian Estala, VP, Field CDO gives an overview of how to seamlessly integrate Data Mesh into your existing ecosystem.
What Are the Three Benefits of Data Mesh?
In this video, Adrian Estala, VP, Field CDO shares three benefits of implementing a Data Mesh as a digital transformation strategy.
Big Data LDN
Starburst’s Lead Solutions Architect Andy Mott explains why Data Mesh isn’t something you can buy off the shelf and what it can do for your organization.
A Primer on Data Mesh
Are you Data Mesh ready? In this session, Andy Mott, Solutions Architect at Starburst explains everything Data Mesh.
Is Data Mesh the Answer to Data Democratization
Accenture’s Cloud First Chief Technologist, Teresa Tung shares how the Data Mesh paradigm can enable data access by unlocking the value of distributed data.
Customer Spotlight: Priceline Achieves Travel Innovation with Starburst
Hear Valli Musti, Engineering Leader at Priceline, share their story of innovation and their data and analytics journey with Starburst with Data Mesh as their core architecture.
Partner Spotlight: Transform your Data into Actionable Business Insights
Ken Seier, North American Strategic Lead, Chief Architect, Data & AI at Insight, highlights how Data Mesh facilitates data sharing and fortifies decision making.
The Potential Impact of Data Mesh Across Industries
In this session, journalist Paul Gillin moderates an engaging discussion between Zhamak Dehghani of Thoughtworks, Richard Jarvis of EMIS Health and Mangesh Patil of Disney.
Starburst is the Analytics Engine for Data Mesh
Data Mesh is a new approach to data architecture and Starburst is the Analytics Engine for Data Mesh. Find out what that means in this video by Justin Borgman, Co-founder, Chairman & CEO, Starburst.
What is Data Mesh?
This video features Justin Borgman, Co-founder, Chairman & CEO, Starburst, as he gives a high-level introduction to the fundamentals of Data Mesh.
Starburst Vision: How We'll Get There
We free our customers to see the invisible and achieve the impossible. Like Shakespeare, Starburst is a five-act play: Act I is Data Lakehouse, Act II is Data Mesh, and then there’s more.
Introduction to Data Mesh
In this video, Zhamak Dehghani gives a high-level overview of the concept, which proposes architectural and organizational changes that transform the way large enterprises analyze data.
How to Build a Foundation for Data Mesh: A Principled Approach
Here Zhamak Dehghani gives an in-depth explanation of how to apply Data Mesh to your current architecture, following the four core principles of Data Mesh.
What Data Mesh Means for Data Analysts
In this panel discussion moderated by ThoughtSpot’s Sean Zinsmeister, panelists and industry experts Zhamak Dehghani, Daniel Abadi, and BoA’s Gareth Stevenson share their perspectives.
What Data Mesh Means for Data Scientists
In this conversation moderated by Red Hat’s Sophie Watkins, panelists and industry experts Zhamak Dehghani, Daniel Abadi, Zalando’s Max Schultze, discuss their perspectives.
CEO Keynote: Achieving a Data Mesh with Starburst
In this talk, Starburst CEO Justin Borgman demystifies Data Mesh and shares concrete ways to begin your journey.
Data Mesh & Data Fabric: A Technical Comparison
In this panel discussion moderated by former Gartner Analyst Sanjeev Mohan, panelists and industry experts Zhamak Dehghani and Daniel Abadi share their perspectives.
Data Product Master Class with Accenture
In this Master Class, Teresa Tung, Accenture's Cloud First Chief Technologist teaches you how to identify and build a data product within your organization.
From Theory to Practice: O'Reilly Market Research
In this talk, Zalando's Max Schultze and Thoughtworks' Arif Wider share their findings and insights from O'Reilly's latest market research report, Data Mesh in Practice.
Data Mesh Governance Strategy with Starburst and Immuta
In this webinar, you’ll learn how Starburst and Immuta can work together to achieve decentralized data access management.
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Watch Datanova 2022: The Data Mesh Summit (All Sessions Available On-Demand Now!)
Data Mesh Blogs
The question of which one to use today (data mesh or data fabric) and whether there is even a question of one versus the other in the first place is not obvious. Ultimately, an optimal solution will likely take the best ideas from each of these approaches.
— Daniel Abadi, Darnell-Kanal Professor of Computer Science, University of Maryland at College Park
With the Data Mesh approach to data management, retailers can more rapidly deploy data strategies that help them better understand their customers and make valuable business decisions.
— Andy Mott MBA, Head of Partner Solutions Architecture and Data Mesh Lead
Data Mesh architecture closes the gap between these transactions and the process of analysis with data ownership granted to individual teams, allowing them to make quick, real-time decisions without the need for data transfer.
— Andy Mott MBA, Head of Partner Solutions Architecture and Data Mesh Lead
Data Mesh, with its deep understanding of technical necessities of data management and breaking down organisational barriers, will and should become the approach of choice if businesses want to strive to become data-driven in their decisions.
— Jess Iandiorio, CMO
The Data Mesh offers a framework for companies to democratise both data access and data management by treating data as a product, curated and governed by the domain experts themselves.
— Justin Borgman, CEO
It’s an acknowledgment that data will be decentralized and that there are advantages to being decentralized, and that really what we’re trying to produce is a single point of access or single point of analytics across all that data regardless of where it lives.
— Justin Borgman, CEO
Treating data as a first-class product drives domain owners to deliver high value and high-quality data for analysis by a wide range of consumers across the organization. I’m proud of the team for delivering what I believe is the first solution of its kind.
— Justin Borgman, CEO
This shift [to decentralized] is business-driven, not IT-driven. This demonstrates the urgency to deliver digital transformation. IT has realized that we can’t migrate to — or sustain — a centralized architecture with the efficiency that the business demands.
— Adrian Estala, VP of Data Mesh Consulting Services
This combination of decentralized data ownership and treating data as a product as part of a Data Mesh approach removes the bottlenecks that come with the traditional data warehousing and data lake models, and in doing so, allows companies to drive faster insights.
— Andy Mott, Partner Solutions Architect
Enterprises have found moving large amounts of data to be cumbersome, expensive and time consuming delaying major business decisions. The Data Mesh concept not only solves this problem but also is a step towards ensuring that data is treated as a first-class product as it is no longer a by-product of an organisation’s operations
— Collen Tartow, Director of Engineering
Companies today realize that it’s a fool’s errand to try to consolidate all of your data into a single data store, and that sentiment is driving the shift to a Data Mesh architecture. Starburst aims to be the de facto query engine for the Data Mesh paradigm.
— Justin Borgman, CEO
Data Mesh is not necessarily about a specific type of technology or code that magically solves data problems at the touch of a button. Instead, it’s about the human side of technology and getting teams to be able to work independently to maximise the value out of data within that organization.
— Justin Borgman, CEO
Achieving a successful Data Mesh architecture requires the ability to access data in disparate systems and sources.
— Matt Fuller, VP of Product
A Data Mesh approach can help financial services better serve its customers and showcase how innovation and success is enabled via a data-driven strategy. Data Mesh decentralises data management and diminishes the impacts of silos and bottlenecks by giving teams ownership, control, and access to their own data.
— Andy Mott, Partner Solutions Architect
With Starburst, TSYS is working towards achieving a sound Data Mesh infrastructure to help their business scale and unlock more data-driven insights.
— Justin Borgman, CEO, Starburst and Mahesh Lagishetty, VP Data Engineering
The data fabric fundamentally is about eliminating human effort, while the data mesh is about smarter and more efficient use of human effort. Of course, it would initially seem that eliminating human effort is always better than repurposing it. However, despite the incredible recent advances we’ve made in ML, we are still not at the point today where we can fully trust machines to perform these key data management and integration activities that are today performed by humans.
— Daniel Abadi, Darnell-Kanal Professor of Computer Science, University of Maryland at College Park
By giving the experts greater control over the data from the beginning of the data management process, businesses will be less likely to lose key data and will be able to bypass common bottlenecks that occur in a centralized approach. The agility of this approach is beneficial for the overall business and will allow for more time to be spent on the analysis, rather than data transfers or depending on the constraint imposed by a centralized IT function.
— Andy Mott, Partner Solutions Architect
As the amount of online data increases and therefore the ability to generate more comprehensive customer insights, it is key to select a data strategy that is focused on removing the impact of inefficient silos and focused on decentralised data for maximum operability and efficiency. This is where data virtualisation can make a significant positive impact, and even more so when it’s part of the adoption of a data mesh based approach.
— Andy Mott, Partner Solutions Architect
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