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.

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

This is a rerelease of a previous episode as we are on a hiatus related to Scott's recent health issues. This is a very important episode for many reasons so please do check it out again :)

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.

Data Mesh Learning Meetup Presentation: https://www.youtube.com/watch?v=7iazNKG8XQo

Sarita's LinkedIn: https://www.linkedin.com/in/saritabakst/

In this episode, Scott interviewed Sarita Bakst, Managing Director and a leader in Firm-wide Data Management at JP Morgan Chase. Sarita was previously on a Data Mesh Learning meetup and is helping lead the firm's data mesh governance charge.

Per Sarita, historically, data governance has meant controls and gatekeeping to most people - typically getting in way of innovation. So there needs to be a focus on changing that narrative, not just through words but actions to show it's not the case. In data mesh, you need to ensure that domains can make good decisions on governance and seek out subject matter experts when it makes sense.

Sarita covered that one of the key issues in the way governance has been done is the people making decisions - the central governance team - don't have the real understanding of the data. When those decisions are put in the hands of the people who really know the data, but with guardrails and guidance, the fear is lifted about can we actually use this data and how. This opens up lots of new opportunities to leverage your data.

Sarita strongly recommends starting with purpose-built data products. Find a use case and build data products to serve that specific. And data products MUST be about unlocking business value. You don't need to serve up all of a domain's data on day one, in version one of that domain's first data product - make it extendible and reusable so you can find additional consumers and expand over time.

Get out of your own way on data governance in data mesh. You are going to learn and your approach will evolve as you learn. It's okay to not know everything upfront, set yourself up to not get in trouble - put the proper guardrails in place - but you won't know everything. Think of designing your risk controls as toll-gates and make sure...

This is a rerelease of a previous episode due to my health related issues. New episodes will begin again in a few weeks. Please enjoy this very important episode of Data Mesh Radio.

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

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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.

Khanh's LinkedIn: https://www.linkedin.com/in/khanhnchau/

In this episode, Scott interviewed Khanh Chau, Lead Architect for the Data Mesh Initiative at Northern Trust.

Khanh believes you have to be passionate about making data better to do a good job implementing data mesh. And it is DEFINITELY a journey so you need patience and vision. Also, each journey is unique, you can't just copy/paste from another organization. You need to make failure okay - but you should look to make it easy to fail fast, measure, and adjust.

Khanh talked about the need for exec buy-in before heading down the data mesh path. They got that exec buy-in by proving that the total cost of ownership of data was quite high as the consumers had to do a LOT of work to get the data to usable.

When speaking internally, the business people were very excited to participate if it meant they could get quality data. Some of the IT/data engineering folks were harder to convince. It was especially hard to get them to shed layers of not-useful technology.

Some IT teams were easier to convince - they had felt the impact of a few too many middle-of-the-night data downtime incidents. Other teams hadn't felt that pain so there were harder to win over. There was also the incentive of additional possibilities - data mesh meant they could do things they couldn't do before.

Khanh talked about making the platform the easy and right path for 80% of use cases. They focused on making things easy to configure; basically: what transformations do you want to do and then it automatically provisions the pipelines. Their goal was to make it easy to make good progress quickly; their time to initial deploy went from 2-3 months per data service to 2-3 weeks per data product and they hope to drive it down further.

Northern Trust has been moving forward with data mesh for about 7 months as part of their high-level digital transformation initiative. On the data side, they had previously focused on data virtualization and data federation but it was not delivering the results they wanted. It was not as scalable as they wanted - it was taking 2-3 months to launch each new data service. They also did not have great information on who was consuming the data and why.

For their data mesh proof of concept, Khanh and team set a timeline of 9 weeks. They needed to prove value by then or data mesh would be a very tough sell internally. Khanh talked about the need to sell data mesh as a paradigm shift in order to get people out of technology-focused thinking.

Northern Trust decided to take a pragmatic approach e.g. not pushing all aspects of data...

Due to health-related issues, we are on a temporary hiatus for new episodes. Please enjoy this release of episode 25, potentially the most important episode of Data Mesh Radio.

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

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

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

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

Due to lingering severe health issues and not trying to rush myself back, I will be doing a 3 week hiatus around new episodes. In that break, I will be rereleasing some old episodes that I think people really need to listen to or possibly reflect on if they haven't listened to them lately. Here's to better health in the near future!

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

Get involved with Data Mesh Understanding's free community roundtables and introductions: https://landing.datameshunderstanding.com/

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.

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.

#251 Panel: Tying the Business Strategy to the Data Strategy and Data Work (and Vice Versa) - Led by Burce Gültekin w/ Ghada Richani, Beth Bauer, and Michael Toland

Burce's LinkedIn: https://www.linkedin.com/in/burcegultekin/

Beth's LinkedIn: https://www.linkedin.com/in/beth-bauer-102449/

Ghada's LinkedIn: https://www.linkedin.com/in/ghada-richani/

Michael's LinkedIn: https://www.linkedin.com/in/mjtoland/

Michael's 'Super Chicken' reference talk by Margaret Heffernan: https://www.ted.com/talks/margaret_heffernan_forget_the_pecking_order_at_work

In this episode, guest host Burce Gültekin, Chief Data and Analytics Officer at FrieslandCampina facilitated a discussion with Ghada Richani, Managing Director, Data & Technology Strategy & Project Management Office at Bank of America (guest of episode #206), Beth Bauer, CEO at her own consulting company PosiROI (guest of episode #218), and Michael Toland, Senior Product Management Consultant & Coach at Pathfinder Product Labs. As per usual, all guests were only reflecting their own views.

The topic for this panel was how do we tie the business strategy all the way down to the data work via the data strategy...

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

Get involved with Data Mesh Understanding's free community roundtables and introductions: https://landing.datameshunderstanding.com/

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.

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.

Christoph's LinkedIn: https://www.linkedin.com/in/christoph-spohr-2a33b619b/

In this episode, Scott interviewed Christoph Spohr, Lead Architect of Big Data Platforms and the Product Owner of Data Mesh at Volkswagen Group. To be clear, Christoph was only representing his own views on the episode.

Quick Note: apologies that Scott's audio is a bit weird, he had yet to build his makeshift sound studio in the Netherlands.

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

1. "There are not solutions, only trade-offs." Understand that nothing is perfect.
2. !Controversial!: Your biggest risk to a use case is choosing the wrong abstraction, the wrong architectural paradigm. When working with a domain, look for a way to achieve the required result that is as close to their existing way of working as possible. Scott note: this can become challenging on finding reusable ways of working if you go too far but greatly smooths domain-level adoption. It's all a tradeoff 😜
3. The second biggest risk is do stakeholders really feel and acknowledge the pain the existing approach/system is causing and want to move? The third biggest risk is about promising things you cannot deliver - obviously look to avoid that.
4. ?Controversial?: A really key aspect of doing data mesh well is having and keeping perspective: doing data mesh is more about "aligning people on a shared vision and not getting lost in the overall process." Don't get so bogged down in exact implementation details if possible.
5. Keep people informed and aligned and start your conversations on clarifying what...

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

Takeaways:

• A data product by the data mesh definition cannot by definition be a silo because it is meant to be consumed by the rest of the organization as a greater part of the picture of the organization. Whether that is true in practice remains to be seen :)
• APIs are the way we've learned in software to interconnect between services, so we need to learn how to leverage the same approaches in data.
• Within a single organization, we may be able to get by without having a great set of industry-wide interconnectivity standards - the company can fully control their own sharing. But, we know that to truly unlock the value of our organizations, cross organization data sharing - in a scalable and useful way - is necessary. So we need better ways to do that - standards and tooling/technology.
• It remains to be seen which will emerge first: the standards or the tooling/technology - a chicken and egg issue there - but they must really must be intertwined to work well.

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.

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

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