Data Mesh Radio

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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.

Amy's LinkedIn: https://www.linkedin.com/in/amy-raygada/

In this episode, Scott interviewed Amy Raygada, Senior Director and Analytics Product Manager at Swiss Marketplace Group (SMG).

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

1. When signing up to do data mesh, you won't exactly know what you are signing up for - it will be different than your expectations in a number of ways so be prepared to be flexible. And it's a marathon, not a sprint. Have patience, you don't need to get it perfect on day one.
2. It's crucial to have a data product owner, someone who can ask the uncomfortable questions and make sure you are actually treating your data as a product. It's easy to get lost in focusing on the technical but that's not what drives the business value.
3. Look to start with a reasonable scope use case instead of a massive challenge. Make it so the teams can learn and iterate because you aren't solving the hardest challenges - yet.
4. Consider starting with a single domain and with a key consumer being that same producing domain. As they learn more about owning data and see value from owning their data, they will be better able to serve other teams too.
5. Spend the necessary time ideating and brain storming before beginning your journey. You want everyone to be working together so a clear initial vision - at least for first steps - is key. But keep updating your prioritizations as you learn more.
6. Data mesh requires major changes for organizations. People aren't good with very abrupt changes so look for the incremental changes where viable. It's okay to take a bit longer if you maintain people's happiness instead of trying to rush to the finish and burn everyone...

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.

What do we need to develop to provide a better experience for data product developers and consumers? How can we make it easy for consumers to move from discover to trust to lean to use? We still have a long long way to go with analytical APIs, they are basically only for sharing raw data at the moment - how can we better share the embedded information? And how can we give data product developers the ability to do the right thing by default where we optimize for ease of use and also for more generalist developers to use - instead of hyper-specialized tools experts? There have been two very separate universes of operational and analytical planes - how do we change that and leverage software engineering practices in analytics?

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.

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.

Alice's LinkedIn: https://www.linkedin.com/in/aliceparker/

No Silver Bullet: Essence and Accident in Software Engineering by Fred Brooks: https://www.cgl.ucsf.edu/Outreach/pc204/NoSilverBullet.html

IBM Research paper mentioned: https://dl.acm.org/doi/10.1145/3290605.3300356

Microsoft Research paper mentioned: https://dl.acm.org/doi/10.1145/2884781.2884783

In this episode, Scott interviewed Alice Parker, Data Engineer at DNB.

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

1. It's easy for people to confuse user experience (UX) and user interface (UI). But UX is far deeper than most understand. We need to design systems and experiences that make working with data - as a producer or a consumer - far easier and more delightful.
2. People are very willing to talk about their challenges - show some empathy and give them the space to talk about what is holding them back and what they could do if you worked with them to address those challenges.
3. Data consumers need three major things to work well with data: 1) domain expertise, 2) time, and 3) to be able to "converse" with their data.
4. Ensure your data quanta - or really any aspect of your data mesh implementation - are documented for all your user personas. There may be different needs for each persona type. A data scientist probably doesn't need as detailed of explanation of...

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. 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.

Dacil's LinkedIn: https://www.linkedin.com/in/daciluhernandez/

In this episode, Scott interviewed Dacil Hernandez, Director of Data and AI for Northwest Europe at Nagarro.

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

1. At the end of the day, tech is the easy part in data. Creating value though data is the hard part. And why do data work if not to create value?
2. It's incredibly easy and pretty common for IT and the business to get disconnected - or never be connected in the first place. Focus on creating and maintaining relationships with a steady flow of context between both sides.
3. Dig into if your business partners actually understand what data ownership means, what it entails. They may be willing but not capable to own data at the start. Work with them to up their capabilities and understanding.
4. Data ownership should not be treated like the "hot potato", being passed to "anyone other than me".
5. Tell your business counterparts "I need your help to help you." You can unlock far more value through collaboration than waiting for requests.
6. Your data strategy should give people FOMO - fear of missing out. Give them incentives that makes it feel like they can't miss out on the value you're creating.
7. !Interesting Idea!: use gamification to find data quality issues. Don't make it a shameful thing, find it and get it remediated and celebrate the people who found it. Look to drive positive energy around your data.
8. Talk to potential data consumers before creating a data quantum or anything in data. You won't know what you can offer that will be valuable to them until you know what they want. So have the conversation.
9. Bad requirements...

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.

Alex's LinkedIn: https://www.linkedin.com/in/alex-bross-33853837/

In this episode, Scott interviewed Alex Bross, VP of Data Engineering at Fifth Third Bank. To be clear, Alex was only representing his own views on the episode.

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

1. Start from empathy. Being able to empathize with someone will give you a far better chance of understanding their context. And analytics is really about understanding what the data shows with the applicable context.
2. There are 3 main barriers to change: logic, credibility, and emotion. Don't skip any of them.
3. Microservices can teach us a LOT about how to distribute data, especially from the people angle. When moving from the monolith with single branch development to API-driven microservices, how did people feel? How did we get them to the right place mentally and capability-wise? We should learn from that and leverage it for data mesh.
4. Don't try to do all your disruption at once. And data mesh is a disruption to the status quo. The business has a cadence, look to fit to that as best as possible.
5. When looking where to begin with something like data mesh, look at need and/or desire. Is there a team that is really struggling and needs change? Or is there a team very willing to try it out?
6. It's very difficult to have positive change with a team that is already struggling. If you are going to work with them now, make sure to be there to help instead of demand change.
7. Catalysts lower the amount of energy needed in a chemical equation. Be a catalyst for change - make it less difficult to change. Focus on that and many - most? - domains will welcome you with open...

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