Data Mesh revisited

Thoughtworks Technology Podcast

Thoughtworks

Careers, Business, 907234, Technology

4.7 • 53 Ratings

🗓️ 15 December 2022

⏱️ 50 minutes

🔗️ Recording | iTunes | RSS

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Summary

Data Mesh is one of the most powerful and widely-discussed concepts to emerge from Thoughtworks in recent years. As the world becomes increasingly aware of the risks and challenges data can pose — from the perspective of both privacy and organizational effectiveness — it has only become more relevant.

In this episode of the Technology Podcast, Zhamak Dehghani (Thoughtworks alumnus and author of O'Reilly's Data Mesh: Delivering Data Driven Value at Scale) and Emily Gorcenski join Rebecca Parsons and Birgitta Böckeler to discuss Data Mesh's place in the industry today, more than three years on from the first time we discussed the topic on the podcast. Together they explore some of the challenges organizations face when adopting it and what its future looks like, as it continues to push the world to rethink data centralization.

Transcript

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0:00.0	Hello, everyone.
0:09.7	My name is Rebecca Parsons.
0:11.3	I'm the chief technology officer for ThoughtWorks,
0:13.5	and I'd like to welcome you to yet another episode
0:16.0	of the ThoughtWorks Technology podcast.
0:19.3	I'm joined today by one of my other co-hosts, Birgitta.
0:22.6	Hi, Birgita. Hi, my name is Begitta Buechler. I'm a technical principle working for ThoughtWorks out of the Berlin, Germany office.
0:30.6	And we are joined today by two guests. One, Jemach Deghani, who is the author of the book on Datamish.
0:42.3	Welcome, Jemak. Wonderful to be here, Rebecca. And we're also joined by Emily Glorzinski,
0:50.3	who I'll let you introduce yourself, actually, Emily. Great. Thanks. It's good to be here.
0:56.0	I am the service line leader for data and AI in ThoughtWorks, Germany.
1:00.0	Great.
1:03.0	And although the book has been out for a while,
1:06.0	we wanted to get together and talk about data mesh, how it's going, where it's going. And so,
1:16.2	Jemak, why don't you start with how did data mesh come about? Well, in fact, it all started around
1:27.2	2018, 2017, with seeing similar patterns with our clients.
1:32.6	I was at the time at ThoughtWorks, and we were working with fairly technologically advanced
1:39.1	organizations that had made quite substantial investments in their data and AI and had quite, you know, quite substantial investments in their data and AI
1:45.0	and had quite, you know, kind of ambitious expectations in getting value from data.
1:52.6	But the pattern that was coming across all of them, that they were failing to materialize value.
1:57.1	And you could measure that failure based on kind of the disproportional ratio of cost to
2:05.0	value, the amount of money they were spending and whether they were competing, you know,
	...

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