Data Mesh Radio

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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.

Andrew's LinkedIn: https://www.linkedin.com/in/andrew-padilla-8988094a/

Datacequia website: https://www.datacequia.com/

Andrew's personal Substack: https://datacequia.substack.com/

Data Mesh Community newsletter Substack: https://datameshlearning.substack.com/

In this episode, Scott interviewed Andrew Padilla, who runs a data and software consulting company - Datacequia - and serves as editor of the Data Mesh Learning community newsletter.

This one is a bit more philosophical about sharing information/knowledge so it's one to sit and think over. Things in quotes are direct from Andrew.

Some key takeaways/thoughts that come from Andrew's view of data mesh and the data space in general:

1. To move from sharing the 1s and 0s of data to actually sharing knowledge, we need to harmonize data, metadata, and code - "the digital embodiment of knowledge". That's where Andrew hopes the mesh data products can head.
2. Software development isn't cutting it for sharing knowledge. Will data product development? Do we need to move to knowledge-centered development instead? Remains to be seen.
3. We still don't know how to model well - in data - what is going on in the real world. What are the experiences of the organization? Can we really define an "organizational experience"? Event storming tries but seems to fall short often.
4. We must learn to treat organizations like living entities. Organizational experiences cross multiple domains and the types of experiences will change, will evolve - possibly quite quickly. We again have to get better at modeling those and evolving how we share knowledge about the experiences.
5. Knowledge graphs are the best way we have currently for combining information across domains. We still haven't fully figured out how to leverage our cross domain knowledge though.
6. Historically, we've bent our ways of working to the limitations of the machines. We need to spend more...

Sign up for Data Mesh Understanding's free roundtable and introduction programs here: https://landing.datameshunderstanding.com/

Please Rate and Review us on your podcast app of choice!

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 / Scott Hirleman. Get in touch with Scott on LinkedIn if you want to chat data mesh.

If you want to learn more and/or join the Data Mesh Learning Community, see here: https://datameshlearning.com/community/

All music used this episode was found on PixaBay and was created by (including slight edits by Scott Hirleman): Lesfm, MondayHopes, SergeQuadrado, ItsWatR, Lexin_Music, and/or nevesf

Sign up for Data Mesh Understanding's free roundtable and introduction programs here: https://landing.datameshunderstanding.com/

Please Rate and Review us on your podcast app of choice!

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 / 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.

Jen's LinkedIn: https://www.linkedin.com/in/jentedrow/

In this episode, Scott interviewed Jen Tedrow, a Product Management Consultant at Pathfinder Product Labs who is currently working with a large client on a data mesh implementation. She was only representing her own perspective in this episode.

Some key takeaways/thoughts from Jen's point of view from the conversation:

1. A data mesh vendor assessment is likely to be different than almost any other vendor assessment you've done before, especially if you aren't evolving something existing. There is so much more to cover and the overall platform needs to meet your needs, integrate with how you handle data on the application side including integrations, comply with your governance standards, fit within budget, etc. That's a lot of needles to thread.
2. Spend considerably more time doing the discovery process in your data mesh vendor assessment than you would for a normal vendor assessment. There are a lot of potentially hidden needs / wants and it is far better to surface them early.
3. By digging deep into stakeholders' desired outcomes, you can understand what you need to deliver but also, you can get insight into driving buy-in. Address the challenges preventing them from the desired outcomes and they will feel seen and heard.
4. As many guests have said, lead with empathy. Change is painful. But if you are realistic with people and make them feel seen and heard, it will be much less painful.
5. When speaking with potential users, again really spend the time to make them feel seen and heard - reflect back to them what you heard. And have them share what is their ideal state. You may not be able to fully deliver on it but it's important to understand where they want to go.
6. As you are learning new information, share that in a continuous stream with stakeholders so they understand the recommendations you are making along the way and at the "end" of the assessment - it doesn't really end when you finish the assessment, so "end".
7. Be prepared for there to be capability gaps - possibly significant - between what you want now and what is available in the market or that you are able to build in your budget. There are just a number of...

Sign up for Data Mesh Understanding's free roundtable and introduction programs here: https://landing.datameshunderstanding.com/

Community open discussion meetup hosted by Eric Broda: https://www.youtube.com/watch?v=OwtQ37WYK1g

Please Rate and Review us on your podcast app of choice!

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 / Scott Hirleman. Get in touch with Scott on LinkedIn if you want to chat data mesh.

If you want to learn more and/or join the Data Mesh Learning Community, see here: https://datameshlearning.com/community/

All music used this episode was found on PixaBay and was created by (including slight edits by Scott Hirleman): Lesfm, MondayHopes, SergeQuadrado, ItsWatR, Lexin_Music, and/or nevesf

Sign up for Data Mesh Understanding's free roundtable and introduction programs here: https://landing.datameshunderstanding.com/

Please Rate and Review us on your podcast app of choice!

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 / 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.

Omar's LinkedIn: https://www.linkedin.com/in/kmaomar/

Omar's State of Data Mesh presentation: https://www.youtube.com/watch?v=S5ABE4bevn4

Adam Grant book Think Again: The Power of Knowing What You Don't Know: https://www.amazon.com/Think-Again-Power-Knowing-What/dp/B08HJQHNH9

Lean Value Tree definition: https://openpracticelibrary.com/practice/lean-value-tree/

In this episode, Scott interviewed Omar Khawaja, Head of Business Intelligence at Roche Diagnostics. To be clear, Omar was only representing his own viewpoints and learnings, not necessarily those of Roche.

Some interesting thoughts/takeaways from Omar's point of view and learnings:

1. If you are going to make progress in a data mesh journey, you must be okay with "good enough". Perfect is the enemy of good and done. Measure, learn, and adjust along the way but get moving and keep moving. It's okay to make mistakes - recognize and correct them.
2. Echoing a number of past guests, change management and organizational challenges will take a large portion of a data mesh implementation leader's time and effort - likely far more than most would expect. Focus on empowering people and showing them why this can work for them. And what it means for them.
3. Data mesh cannot be your entire data strategy. If you are implementing data mesh, it must only be part of your data strategy. Start from the why. Why undertake something as transformational and difficult as implementing data mesh? What business value will it deliver?
4. Data-as-a-product thinking is the true heart of a data mesh implementation. It's far more than just creating data products. Data product discovery is crucial, much like discovery in regular product management. Take considerable learnings from product management in other disciplines.
5. Focus on outcomes in day-to-day data work. What are you trying to deliver? What is the value in...

Sign up for Data Mesh Understanding's free roundtable and introduction programs here: https://landing.datameshunderstanding.com/

Please Rate and Review us on your podcast app of choice!

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 / Scott Hirleman. Get in touch with Scott on LinkedIn if you want to chat data mesh.

If you want to learn more and/or join the Data Mesh Learning Community, see here: https://datameshlearning.com/community/

All music used this episode was found on PixaBay and was created by (including slight edits by Scott Hirleman): Lesfm, MondayHopes, SergeQuadrado, ItsWatR, Lexin_Music, and/or nevesf

Sign up for Data Mesh Understanding's free roundtable and introduction programs here: https://landing.datameshunderstanding.com/

Please Rate and Review us on your podcast app of choice!

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 / 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

Dave's LinkedIn: https://www.linkedin.com/in/davidcolls/

Zhamak's data mesh book: https://www.oreilly.com/library/view/data-mesh/9781492092384/

Building Evolutionary Architecture book: https://www.oreilly.com/library/view/building-evolutionary-architectures/9781491986356/

Team Topologies book: https://teamtopologies.com/book

The Agile Triangle regarding helping you decide how thin to slice: https://www.projectmanagement.com/blog/blogPostingView.cfm?blogPostingID=5325&thisPageURL=/blog-post/5325/The-Agile-Triangle#_=_

In this episode, Scott interviewed Dave Colls, Director of Data and AI at Thoughtworks Australia. Scott invited Dave on due to a few pieces of content including a webinar on fitness functions with Zhamak in 2021. There aren't any actual bears, as guests or referenced, in the episode :)

To start, some key takeaways/thoughts and remaining questions:

1. Fitness functions are a very useful tool to assess questions of progress/success at a granular and easy-to-answer level. Those answers can then be summed up into a greater big picture. You should start with fitness functions early in your data mesh journey so you can also measure your progress along the way. To develop your fitness functions, ask "what does good look like?"
2. Focus your fitness functions on measuring things that you will act on or are important to measuring success. Something like amount of data processed is probably a vanity metric - drive towards value-based measurements instead.
3. Your fitness functions may lose relevance and that is okay. You should be measuring how well you are doing overall, not locking on to measuring the same thing every X time period. What helps you assess

Sign up for Data Mesh Understanding's free roundtable and introduction programs here: https://landing.datameshunderstanding.com/

Sign up here for a Data Mesh Therapy session here: https://calendly.com/data-as-a-product/data-mesh-therapy

Please Rate and Review us on your podcast app of choice!

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 / Scott Hirleman. Get in touch with Scott on LinkedIn if you want to chat data mesh.

If you want to learn more and/or join the Data Mesh Learning Community, see here: https://datameshlearning.com/community/

All music used this episode was found on PixaBay and was created by (including slight edits by Scott Hirleman): Lesfm, MondayHopes, SergeQuadrado, ItsWatR, Lexin_Music, and/or nevesf

Sign up for Data Mesh Understanding's free roundtable and introduction programs here: https://landing.datameshunderstanding.com/

Please Rate and Review us on your podcast app of choice!

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 / 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.

Jay's LinkedIn: https://www.linkedin.com/in/jaysen2/

Posts by Jay:

Next-Gen Data Movement Platform at PayPal: https://medium.com/paypal-tech/next-gen-data-movement-platform-at-paypal-100f70a7a6b

How PayPal Moves Secure and Encrypted Data Across Security Zones: https://medium.com/paypal-tech/how-paypal-moves-secure-and-encrypted-data-across-security-zones-10010c1788ce

The Evolution of Data-Movement Systems: https://jaysen99.medium.com/evolution-of-data-movement-f12614d6e9de

In this episode, Scott interviewed Jay Sen, Data Platforms & Domain Expert/Builder and OSS Committer. While Jay currently works at PayPal, he was only representing his own view points.

Some key takeaways/thoughts from Jay's view:

1. When you get to a certain scale, any central team should focus on, as Jay said, "Empower people, don't try do their jobs." That's how you build towards scale and maintain flexibility - your centralized team likely won't become a bottleneck if they aren't making decisions on behalf of other teams.
2. To actually empower other teams, dig into the actual business need and work backwards to a solution that can solve that. If there is a solution already in place that isn't working any more, look to find ways to augment that rather than trying to replace or reinvent the wheel.
3. Self-service is a slippery slope - it often solves the immediate problem of time to market but also creates next level challenges. A big issue is that when you remove the friction to data access, you are throwing challenge of finding right data on consumers plate.
4. Data contracts are great when everybody aligns on a single contract and there are enough tools to support the contracts. But they also create a proliferation of data to enforce the contracts required by multiple consumers - thus,...

Sign up for Data Mesh Understanding's free roundtable and introduction programs here: https://landing.datameshunderstanding.com/

Please Rate and Review us on your podcast app of choice!

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 / Scott Hirleman. Get in touch with Scott on LinkedIn if you want to chat data mesh.

If you want to learn more and/or join the Data Mesh Learning Community, see here: https://datameshlearning.com/community/

All music used this episode was found on PixaBay and was created by (including slight edits by Scott Hirleman): Lesfm, MondayHopes, SergeQuadrado, ItsWatR, Lexin_Music, and/or nevesf