eBook
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!
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
Loading...
Free Data Mesh Books
How Starburst helps with Data Mesh
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.
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.
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.
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.
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.
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.
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.
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.
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
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.
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.
Achieving a successful Data Mesh architecture requires the ability to access data in disparate systems and sources.
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.
With Starburst, TSYS is working towards achieving a sound Data Mesh infrastructure to help their business scale and unlock more data-driven insights.
With Starburst, TSYS is working towards achieving a sound Data Mesh infrastructure to help their business scale and unlock more data-driven insights.
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.
Get in touch
Want to try Starburst? Have questions? We're here to help.
