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Provided as a free resource by Data Mesh Understanding / Scott Hirleman. Get in touch with Scott on LinkedIn if you want to chat data mesh.

Transcript for this episode (link) provided by Starburst. See their Data Mesh Summit recordings here and their great data mesh resource center here.

Relevant Links:

Jesse's Data Teams Book: https://www.amazon.com/Data-Teams-Management-Successful-Data-Focused-ebook/dp/B08JLFTPBV

Big Data Institute website: https://www.bigdatainstitute.io/

Data Dream Team podcast: https://sodapodcast.libsyn.com/site

Jesse's LinkedIn: https://www.linkedin.com/in/jessetanderson/

In this episode, Scott interviewed Jesse Anderson, Managing Director at consulting company Big Data Institute, host of the Data Dream Team podcast, and author of 3 books, most recently Data Teams.

To start, a few takeaways from Jesse's perspective on the choosing technology side:

• You should make sure you have the right team in place to make good technology decisions - the team needs to be in place first
• Before selecting any technology, it's crucial to understand what you are trying to accomplish. And to understand that the technology will provide help in addressing the challenge but won't solve anything itself
• Focus on: is this the right tool or solution for us now and in the future? What is the roadmap and vibrancy of the solution?
• "Technology must earn its keep", meaning you should understand the total cost of ownership and what is your expected return on investment
• Data tooling cycles are probably going to be 10 years at the most - prepare for obsolescence so you aren't overly reliant on any one technology

And some takeaways from Jesse's point of view on decentralizing data teams:

• Currently, software engineers aren't ready to be data product developers so you'd need embedded data engineers to handle creating and maintaining data products in data mesh
• But many data engineers are not willing to be embedded into domains
• Managing the dotted line versus solid line of reporting between a functional team and the domain is very difficult
• There are a number of cracks where crucial data can