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.

Jill's LinkedIn: https://www.linkedin.com/in/jillianmaffeo/

Developing Interoperable Channel Domain Data (blog post): https://vista.io/blog/developing-interoperable-channel-domain-data

In this episode, Scott interviewed Jill Maffeo, Senior Data Product Manager at Vista.

Before jumping in, Jill gives a lot of very useful examples of outcomes they've been able to drive that could be abstracted to apply to your own organization's business challenges. Outcomes like better customer segmentation, faster time to launch new offerings, etc. If you are having difficulty with stakeholder buy-in, especially for someone in marketing, this episode could help you frame things in their language.

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

1. "When you're thinking about interoperability, it's just playing nice, right?" If you think of interoperability as a key part of your culture, it's easier to implement. Let people know why interoperability is good for them and the whole company.
2. Taxonomies help drive interoperability because there is already an established language even if things don't fit perfectly. New concepts can emerge and your taxonomies should change. But it makes the interoperability discussions have at least a common starting point.
3. Taxonomies are a living thing - make sure they aren't overly rigid and be prepared to continually evolve and improve them.
4. Within your taxonomy structure, if there is a reason for things to be unique for a domain or use case, that is okay. Look for potential ways to also convert that data to best fit your...

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.

Carlos' LinkedIn: https://www.linkedin.com/in/carlos-saona-vazquez/

In this episode, Scott interviewed Carlos Saona, Chief Architect at eDreams ODIGEO.

As a caveat before jumping in, Carlos believes it's too hard to say their experience or learnings will apply to everyone or that he necessarily recommends anything they have done specifically but he has learned a lot of very interesting things to date. Keep that perspective in mind when reading this summary.

Some key takeaways/thoughts from Carlos' point of view:

1. eDreams' implementation is quite unique in that they were working on it without being in contact with other data mesh implementers for most of the last 3 years - until just recently. So they have learnings from non-typical approaches that are working for them.
2. You should not look to create a single data model upfront. That's part of what has caused such an issue for the data warehouse - it's inflexible and doesn't really end up fitting needs. But you should look to iterate towards that standard model as you learn more and more about your use cases.
3. ?Controversial?: Look to push as much of the burden as is reasonable onto the data consumers. That means the stitching between data products, the compute costs of consuming, etc. They get the benefit so they should be taking on the burden. Things like data quality are still on the shoulders of producers.
4. You should provide default values for your data product SLAs. It makes the discussion between consumers and producers far easier - is the default good enough or not?
5. ?Extremely Controversial?: At eDreams, you cannot publish data in your data product that you are not generating. In derived domains (e.g.,

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.

Adelle's LinkedIn: https://www.linkedin.com/in/adelle-mcdonald-79a9a2139/

In this episode, Scott interviewed Adelle McDonald, Customer and Origination Lead at ANZ Plus, a bank in Australia and New Zealand.

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

1. To drive buy-in, the 1:1 conversations with domain owners - the business leaders - you will have to tailor your conversations to each person. Listen to their pain and reflect it back to them.
2. Focus on an ability to quickly pivot with low cost. That can mean things aren't as product-worthy to start but it means you can evolve towards value more quickly.
3. Addressing domain owners' pain points gets them looking at you as a partner. They will be much more willing to work with you, especially as you partner to provide actionable insights.
4. ?Controversial?: ANZ Plus is embedding data leads into domains to handle the data quanta for the domain and also build the team what they need from data. As part of that, they are slowly building up the domains' capabilities to handle their own data. This minimizes friction and creates buy-in but is likely not long-term sustainable - ownership will need to be transferred.
5. Very important to tie the data quanta to use cases - driving value for users means focusing on use cases.
6. Developers or software engineers owning data is complicated. Make it so they can start to make small changes and learn in a safe way instead of dumping all ownership on them at once. Ownership and knowledge aren't a switch you flip.
7. Using a git-based, pull request approach, developers can attempt data work without manual stitching so they learn to do the work themselves; but it can...

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.

Gunjan's LinkedIn: https://www.linkedin.com/in/gunjanaggarwal/

Gunjan's Medium: https://gunjan-aggarwal.medium.com/

In this episode, Scott interviewed Gunjan Aggarwal, Head, Digital Data Products and MarTech Strategy at Novartis. To be clear, she was only representing her own views on the episode.

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

1. Set your overall data product strategy - for when you are in stage 2, going wider with data mesh - earlier in your journey than many may think. It's easy to focus only on use cases instead of the bigger picture.
2. Make sure to align early on who owns what - what are the clear boundaries between roles. Otherwise, with the amount of change data mesh drives, there will likely be unnecessary chaos. Get specific.
3. Don't fall to the 'Data Field of Dreams' - "if you build it, they will come." Focus on building to actual problem statements. Involve people early, make them accountable, give them skin in the game and they will care.
4. "The more you ask why, the more clarity you will get." Really dig in deep into the reasoning for creating new data products or ARDs (analytics ready datasets). If we have this data product, what will it unlock for us?
5. It's crucial to avoid the trap of building data products specifically to use cases. You must have the bigger picture in mind and focus on reusability instead of only solving one set of challenges. Can you extend an existing data product?
6. Data people should have domain knowledge where possible. That way, they can push back on requirements that don't make economic sense, that don't...

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.

Dmitriy's Twitter: @squarecog / https://twitter.com/squarecog

The Missing README book: https://themissingreadme.com/

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

In this episode, Scott interviewed Dmitriy Ryaboy, CTO at Zymergen and co-author of the book The Missing README.

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

1. Organizational design and change management is "like a knife fight" - you are going to get cut but if you do it well, you can choose where you get cut. There is no perfect org, and there will be pain somewhere but you can influence what will hurt, and make it not life-threatening.
2. There is too much separation between data engineering and software engineering. Data engineering is just a type of software engineering with a focus on dealing with data. We have to stop treating them like completely different practices.
3. When communicating internally, always focus on telling people the why before you get to the how. If they don't get why you are doing it, they are far less likely to be motivated to address the issue or opportunity. This applies to getting teams to take ownership of the data they produce, but also to everything else. There is often a rush to use tech over talk. Conversation is a powerful tool and will set you up so your tools can help you address the challenges once people are aligned. Paving over challenges with tech will not go...

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