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. You can download their Data Mesh for Dummies e-book (info gated) here.

Nicola's website: https://www.nicolaaskham.com/

The Data Governance Podcast: https://www.nicolaaskham.com/podcast

Nicola's LinkedIn: https://www.linkedin.com/in/nicolaaskham/

In this episode, Scott interviewed Nicola Askham, a data governance consultant known simply as The Data Governance Coach and host of The Data Governance Podcast.

Some key takeaways/thoughts from Nicola's point of view:

1. The key point of data governance: ensure the data we use is the right data for the right people to better address business challenges. Everything you do with governance should circle back to that.
2. In doing data governance right, you need to set yourself up to take in feedback and iterate. You absolutely won't get everything right upfront. It's crucial to set expectations that your data governance approach will evolve as you learn more.
3. If you see data mesh as being about making better data more accessible to your current data consumers, that's a very big opportunity wasted. Aim to significantly expand your pool of data citizens. Not everyone should be a data scientist but data should play a role in much more people's jobs.
4. To get going in data mesh, you need to get your data governance to "good enough" and start moving forward. Think about what you need - is it the very complicated standard to last the next decade or is it about getting people to understand and trust the data they can now access? Probably the second...
5. To drive buy-in for data governance, you should tailor your message to the...

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. You can download their Data Mesh for Dummies e-book (info gated) here.

Winfried's LinkedIn: https://www.linkedin.com/in/winfried-adalbert-etzel/

MetaDAMA podcast (episodes in both English and Norwegian): https://podcasts.apple.com/us/podcast/metadama-en-helhetlig-podcast-om-data-management-i-norden/id1572639573

In this episode, Scott interviewed Winfried Etzel, Information Strategy Consultant at Bouvet, Board member of DAMA Norway, and host of the MetaDAMA podcast.

Some key takeaways/thoughts from Winfried's point of view:

1. Transformation teams - a team that helps domains to transform and upskill by embedding in the domain for a time - is an exciting pattern for data mesh.
2. Transformation teams can collect information more easily and find patterns as they are closely collaborating with more domains.
3. Think of transformation teams like a personal trainer - they help you get in shape so you learn what exercises to do and how but then you can work on your own. And you can engage them again if you need more help.
4. How can we give guidance and enable change at the same time - the transformation teams shouldn't do the work for the domains but need to work with them. Can we go broad in the organization if we only have a limited number of transformation teams? Do we need to be in that much of a hurry where that's an issue?
5. There's definitely some vendor washing going on around data mesh. It's often difficult to determine what is new and what they've recycled to sound new.
6. In data, we should look to take many learning from software engineering but also other...

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. You can download their Data Mesh for Dummies e-book (info gated) here.

Blanca's LinkedIn: https://www.linkedin.com/in/blancamayayo/

Pablo's LinkedIn: https://www.linkedin.com/in/pablodoval/

In this episode, Scott interviewed Blanca Mayayo - Product Manager, Data Platforms - and Pablo Alvarez Doval - Lead of Data Platforms and Principal Data Architect - at Plain Concepts.

From here forward in this write-up, B&P will refer to Blanca and Pablo rather than trying to specifically call out who said which part.

Some key takeaways/thoughts from B&P's point of view:

1. It's easy to fall into adding fit-for-purpose capabilities to your data platform but don't. Stay focused on managing your platform as a product - all aspects of it have lifecycles - and you can't try to fit every use case, especially before there is a need.
2. If transformation, especially data transformation, is not tied to the business strategy, that is a major recipe for failure. You likely won't deliver good business outcomes.
3. "Beware the proof of concept" - too many try to do a proof without the actual concept. What are you trying to prove and how will you decide/measure if you proved it?
4. You can have everything necessary for a data initiative to succeed lined up - the sponsors, the will, the budget - and still fail. Nothing is 100%.
5. Three common data initiative failure modes: 1) focusing only on the technology aspect and not does it meet needs and can we maintain and pay for it; 2) only treating it as an urgent tactical needs instead of playing into the broader data strategy; and 3) not considering how to actually do change management.
6. Your platform is a...

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

Sponsored by NextData, Zhamak's company that is helping ease data product creation.

For more great content from Zhamak, check out her book on data mesh, a book she collaborated on, her LinkedIn, and her Twitter.

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

Data Mesh Radio 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.

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. You can download their Data Mesh for Dummies e-book (info gated) here.

Get in touch with Simon and Sunny: [email protected]

A webinar (info gated) Sunny and Simon did on data mesh: https://events.esynergy.co.uk/data-mesh-experimentation-to-industrialisation-on-demand

Simon's LinkedIn: https://www.linkedin.com/in/simon-massey-82718a3/

Sunny's LinkedIn: https://www.linkedin.com/in/sunnysjaisinghani/

In this episode, Scott interviewed Sunny Jaisinghani and Simon Massey who are both Principal Consultants at the consulting company esynergy. They have been involved in multiple data mesh implementations including at a large bank. This episode could also have been titled: Aligning Incentives, Reducing Friction, and Continuous Improvement/Value Delivery but it doesn't roll off the tongue very well.

From here forward in this write-up, S&S will refer to Simon and Sunny rather than trying to specifically call out who said which part as that leads to confusion.

Some key takeaways/thoughts from S&S's points of view:

1. We are all still early in our learnings about how to do data mesh well. There is still a ton left to learn. Which is why people should share what they are learning more broadly. Helping others will help you.
2. Data mesh, whether it's your overall implementation, your platform, your data products, your ways of working, etc. is all about evolution, incremental improvement, iteration, etc. You...

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. You can download their Data Mesh for Dummies e-book (info gated) here.

Data Product Manager Role on Alla's team: https://jobs.ecolab.com/job/15770737/data-product-manager-barcelona-es/

Alla's LinkedIn: https://www.linkedin.com/in/allahale/

In this episode, Scott interviewed Alla Hale, a Data Product Manager at Ecolab. To be clear, she was only representing her own views rather than anything on behalf of the company. She is hiring in Barcelona as well, see here

Some key takeaways/thoughts from Alla's point of view:

1. The most useful question in your quiver as a data producer is "what value would having this unlock for you?" It's not about pushing back, it's about skipping to collaborative negotiation. How can you work together to unlock business value?
2. It's important to remember this when there is a data request: "they are coming to you because they need your help." Act accordingly - with empathy and patience.
3. You need to really consider your data user experience (DUX) for your data products. How can you quickly get people past figuring out "what the product is" to leveraging the data product to drive value? You want users to enjoy using your data product.
4. User stated requirements often do not match actual user needs. To maximize the return on your data work, look to exchange context to find the needs instead of just taking requirements at face value. And do so with patience and empathy.
5. No prototype, no meeting = having something tangible - even if that is simply a...