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. 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.

Ale's LinkedIn: https://www.linkedin.com/in/alejandracabre/

In this episode, Scott interviewed Ale Cabrera, Senior Data Quality Product Manager at Clearbit. To be clear, she was only representing her own views on the episode.

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

1. A key part of understanding what data work will be impactful is a simple phrase: "Is my understanding correct?" Putting out there what you took in and making sure you're on the same page will save a ton of time and headaches!
2. Her advice to her past self: In data, far too often, we try to jump to solutioning instead of really taking the time to understand the problem. Start from understanding the problem and assessing it first.
3. It's very easy to make data say something that it's not actually reflecting. Quality isn't just about accuracy or similar metrics, sometimes there are intangible aspects around correctness that people get but usually can't measure.
4. In data work, many people miss two crucial aspects - the voice of the customer and the why. If you build the greatest thing ever but it isn't what the customer wants, it won't be used. Similarly, if you focus on the work and not the target outcome, your results are likely to be subpar.
5. If you want to prove data work return on investment, try to associate it to a key company metric and talk about how improving that metric will drive better business outcomes.
6. When you want to prove out the value of data quality, attach quality issues to direct business challenges or goals. It’s easy if you are a company selling data but you have to understand why bad quality...

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

Key takeaways:

• As mentioned last time, at the start, it's more important to start measuring something than it is to measure the right things. Do NOT let analysis paralysis hold you back. Start measuring early to figure out what actually matters and that will also change over time.
• Similarly, your success metric measurement framework will probably suck to start. Oh well, get to measuring.
• Use fitness functions.
• Data mesh really is a journey and so will be how you measure success. You will need to find small and simple ways to measure. Don't get bogged down. Your measurements will be rough and kinda depressing with the amount of challenges to tackle at the start. Just understand this is about how well you are doing, not how complete you are - there is always more to do!
• Good metrics to consider for the platform success metrics: satisfaction, time to deploy new products, time to update existing ones, ease of use - which kind of blends into all the others -, searchability/discoverability, ease of interconnection, mean-time-to-detect and mean-time-to-recovery from issues, governance, guardrails, and automation/helpful artifacts.
• Look to measure friction and how you reduce it and if possible - I have no great ideas here - what is the extra value add to the business, something that the platform was the genesis of? Maybe that's suggesting data products?
• Lastly, reflect back on how far you've come, we often forget to do that!

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!

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.

#252 Designing and Building a Better Data Governance Approach - Interview w/ Lauren Maffeo

Kinda's LinkedIn: https://www.linkedin.com/in/kindamaarry/

In this episode, Scott interviewed Kinda El Maarry PhD, Director of Data Governance at Prima. To be clear, she was only representing her own views on the episode.

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

1. Always be assessing data literacy gaps and work to address them. Gaps don't have to be a bad thing, they are a chance for your people to grow! But ignore them at your own peril :)
2. A key aspect of your job as someone on the central governance team - or anyone managing a governance function - is to reduce friction, not add overhead. It can be hard to do that at the start of a journey but it should be a north star focus.
3. The phrase 'data governance' still has a stigma for many people from what often happens with a central-only approach to governance - processes and rules divorced from the actual business processes and the data which creates bottlenecks and headaches.
4. The federation of governance in data mesh helps address the bottlenecks but it introduces a new layer of complexity which can also cause some fear.
5. ?Controversial?: If you are asking people to take on ownership of data, you must make sure their line of business/part of the org has the actual capabilities to do so. Otherwise, they will greatly struggle to own and are likely to push back.
6. Don't talk about governance in the weeds to people, the toolbox talks, the policies and standards. Focus on what are you trying to achieve with...

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

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.

Samia's LinkedIn: https://www.linkedin.com/in/samia-r-b7b65216/

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

Sheetal's Links:

Sheetal's LinkedIn: https://www.linkedin.com/in/sheetalpratik/

First Paper at ICEB Conference: https://easychair.org/publications/preprint/qZ3m

Interview in Harvard Business Review: https://hbr.org/resources/pdfs/comm/BeyondTechnology_CreatingBusinessValuewithDataMesh.pdf

Medium Blog on Saxo Bank Implementation: https://blog.datahubproject.io/enabling-data-discovery-in-a-data-mesh-the-saxo-journey-451b06969c8f

In this episode, guest host Samia Rahman, Director of Enterprise Data Strategy, Architecture, and Governance at life sciences company Seagen (guest of episode #67) facilitated a discussion with Sheetal Pratik, Director Engineering and leading India Data Integration Platform at Adidas (guest of episode #24), and Khanh Chau, Director of Cloud Data Architecture at Grainger (guest of episode #44). As per usual, all guests were only reflecting their...

You can simply use the link here https://us06web.zoom.us/j/87380091930?pwd=NVhUS3ZDOS9hSFFBbU1sQm9HQUJHZz09 or find a link on LinkedIn events: https://www.linkedin.com/events/weeklydatameshopenroundtable-da7091373106551734272/comments/

Link to past recordings playlist: https://www.youtube.com/playlist?list=PL9tZROTS_Pi7TjjhLR-sCtwQVeth6Jv7e

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.

Benny's LinkedIn: https://www.linkedin.com/in/bennybenford/

Benny's Substack: https://www.datent.com/p/elevating-data-to-a-profession-why

In this episode, Scott interviewed Benny Benford, the former CDO at Jaguar Land Rover (JLR) and who is currently building out a community around data transformation. To be clear, he was only representing his own views on the episode.

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

1. !Controversial!: As a data leader, if you want to be effective, you will have to focus much more on what role data work plays in the organization rather than the data work itself. It's about partnering and communication, not SQL and LLMs. That can be a hard lesson but it's crucial to being successful.
2. ?Controversial?: It's easy to try - and common to want - to separate data culture and organizational culture but it doesn't really work. "Data culture is … an aspect of your organizational culture that you're trying to build and create."
3. A guidepost for your transformation journey: "If you want to go fast, go alone; if you want to go far, go together."
4. The data team can be leaders in transforming the organization but they must do it in collaboration, not just going out as pioneers 'to set an example' or something. Absolutely partner with your transformation org if you have one.
5. When you align your data culture transformation to the overall organization transformation messaging, you aren't fighting for attention to a different message. You are using 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

Takeaways:

• It's important to understand that we need enablement to do data mesh well. That is enablement through technology and enablement through organizational approaches/behavior changes. Doing only one will likely not work.
• "...they need to move fast, they cannot be bogged down by centralization of any kind, organization or technology." Scott note: I will say we discuss later the need for centrally provided enablers but central bottlenecks are the speed and flexibility killer, look to prevent and remove them where possible.
• People want to simply produce data as a normalized process of doing their job and make it consumable for the rest of the organization. How can we enable that? Why is it so tough? How do we make it interoperable - and more importantly interconnectable - too?
• Right now, the missing core component to do data mesh well is an easy ability to create and manage data products. Everyone is having to cobble things together and then trying to layer on the observability, the access control, the interconnectivity, etc. But it's built on a shaky foundation.

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