1h 1m
#304 Getting Your Data Mesh Journey Moving Forward - Interview w/ Chris Ford and Arne Lapõnin Data Mesh Radio
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- Tecnología
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Get involved with Data Mesh Understanding's free community roundtables and introductions: https://landing.datameshunderstanding.com/
If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see here
Episode list and links to all available episode transcripts here.
Provided as a free resource by Data Mesh Understanding. Get in touch with Scott on LinkedIn.
Transcript for this episode (link) provided by Starburst. You can download their Data Products for Dummies e-book (info-gated) here and their Data Mesh for Dummies e-book (info gated) here.
Arne's LinkedIn: https://www.linkedin.com/in/arnelaponin/
Chris' LinkedIn: https://www.linkedin.com/in/ctford/
Foundations of Data Mesh O'Reilly Course: https://www.oreilly.com/videos/foundations-of-data/0636920971191/
Data Mesh Accelerate workshop article: https://martinfowler.com/articles/data-mesh-accelerate-workshop.html
In this episode, Scott interviewed Arne Lapõnin, Data Engineer and Chris Ford, Technology Director, both at Thoughtworks.
From here forward in this write-up, I am combining Chris and Arne's points of view rather than trying to specifically call out who said which part.
Some key takeaways/thoughts from Arne and Chris' point of view:
Before you start a data mesh journey, you need an idea of what you want to achieve, a bet you are making on what will drive value. It doesn't have to be all-encompassing but doing data mesh can't be the point, it's an approach for delivering on the point 😅Relatedly, there should be a business aspiration for doing data mesh rather than simply a change to the way of doing data aspiration. What does doing data better mean for your organization? What does a "data mesh nirvana" look like for the organization? Work backwards from that to figure where to head with your journey.A common early data mesh anti-pattern is trying to skip both ownership and data as a product. There are existing data assets that leverage spaghetti code and some just rename them to data products and pretend that's moved the needle."A data product is a data set + love." The real difference between a data product and a data set is that true ownership and care.?Controversial?: Another common mesh anti-pattern is trying to get too specific with definitions or...
Please Rate and Review us on your podcast app of choice!
Get involved with Data Mesh Understanding's free community roundtables and introductions: https://landing.datameshunderstanding.com/
If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see here
Episode list and links to all available episode transcripts here.
Provided as a free resource by Data Mesh Understanding. Get in touch with Scott on LinkedIn.
Transcript for this episode (link) provided by Starburst. You can download their Data Products for Dummies e-book (info-gated) here and their Data Mesh for Dummies e-book (info gated) here.
Arne's LinkedIn: https://www.linkedin.com/in/arnelaponin/
Chris' LinkedIn: https://www.linkedin.com/in/ctford/
Foundations of Data Mesh O'Reilly Course: https://www.oreilly.com/videos/foundations-of-data/0636920971191/
Data Mesh Accelerate workshop article: https://martinfowler.com/articles/data-mesh-accelerate-workshop.html
In this episode, Scott interviewed Arne Lapõnin, Data Engineer and Chris Ford, Technology Director, both at Thoughtworks.
From here forward in this write-up, I am combining Chris and Arne's points of view rather than trying to specifically call out who said which part.
Some key takeaways/thoughts from Arne and Chris' point of view:
Before you start a data mesh journey, you need an idea of what you want to achieve, a bet you are making on what will drive value. It doesn't have to be all-encompassing but doing data mesh can't be the point, it's an approach for delivering on the point 😅Relatedly, there should be a business aspiration for doing data mesh rather than simply a change to the way of doing data aspiration. What does doing data better mean for your organization? What does a "data mesh nirvana" look like for the organization? Work backwards from that to figure where to head with your journey.A common early data mesh anti-pattern is trying to skip both ownership and data as a product. There are existing data assets that leverage spaghetti code and some just rename them to data products and pretend that's moved the needle."A data product is a data set + love." The real difference between a data product and a data set is that true ownership and care.?Controversial?: Another common mesh anti-pattern is trying to get too specific with definitions or...
1h 1m