Demystifying the Secrets of Data Mesh with Snowflake’s Kent Graziano
Hashmap on Tap Ep. 95
“It’s a concept of how we think about organizing the data and how we are going to empower organizations with access to that data — that is the underpinning of all of this [data mesh].” — Kent Graziano, Chief Technical Evangelist at Snowflake
In the data community, there is a struggle to deliver data products quickly and efficiently. Could using an approach based on the up-and-coming principles of data mesh be the way to help solve this problem?
On a recent episode of Hashmap on Tap, Kelly Kohlleffel welcomes returning guest, Kent Graziano, Chief Technical Evangelist at Snowflake to discuss everything you need to know about the relatively new topic of data mesh. If you think Kent’s name sounds familiar, that’s probably because this isn’t Kent’s first time being on Hashmap on Tap — it’s actually his third! On tap for this episode for Kent is a returning favorite, HEB Grapefruit Sparkling Water, and for Kelly, HEB Lemon Strawberry Sparkling Water.
Kent kicks off the episode by describing how data mesh appeared on his personal radar, and he details his approach to educating himself about this new topic. Kent shares personal recommendations on learning materials from the data mesh community (links can be found at the end of the article) and what can be learned from each of them.
So what is data mesh?
Data mesh is emerging as a way to solve particular problems with data. According to Kent, data mesh is definitely not a technology, but it’s somewhere between a framework and architecture. In the podcast episode, Kent shares how he discovered a Flexport webinar that presents data mesh as a sociotechnical problem, and you’ll want to listen to the episode to hear his reasons on why he agrees with that description.
What are the four principles of data mesh?
- Domain-centric ownership and architecture
- Data as a product
- Self-serve infrastructure as a platform
- Federated governance
Kent delivers a thorough breakdown of the fundamentals of each of these four principles in the context of data mesh. He has spent the last six years with Snowflake, and he draws from this experience, as well as at other companies, to share unique perspectives on how these principles can be used as a way to solve particular problems with data.
Are the principles of data mesh at odds with that of traditional data management? How is Snowflake’s platform incorporating the principles of data mesh?
To answer this question from Kelly about what data mesh means for traditional data management, Kent puts things in perspective by sharing examples of Snowflake customers that are already using a data mesh approach. He uses his intimate knowledge of Snowflake’s platform, and the Snowflake Data Cloud, to give opinions on how the Snowflake Data Marketplace aligns with the four principles of data mesh, as well as Snowflake’s approach to rethinking traditional data management.
In addition to exploring the topic of data mesh, Kelly and Kent candidly discuss approaches to solving problems in the data community, including what perspective Kent uses to solve problems, how to do something rational to solve that problem, and how to avoid ending up on the list of failures in the history of the data industry.
This episode is jam-packed with useful information and advice, along with fun conversations, about the truly up-and-coming topic of data mesh. Kent’s genuine interest shows through in the way that he shares information, and at the end of the episode, you’ll understand why he has “Evangelist” in his title — this is certainly an episode that you won’t want to miss!
Listen to the episode here:
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Kent’s Recommendations on Data Mesh Resources:
- Learn more about Data Mesh
- Read Zhamak Dehghani’s book, Data Mesh Principles
- Read these blog posts from Snowflake about the key principles of data mesh and data mesh in the data cloud
Additional Resources:
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