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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.

Transcript for this episode (link) provided by Starburst. You can download their Data Products for Dummies e-book (info-gated) here and their Data Mesh for Dummies e-book (info gated) here.

Saba's LinkedIn: https://www.linkedin.com/in/sabaishaq/

Decide Data website: ttps://www.decidedata.com/

In this episode, Scott interviewed Saba Ishaq, CEO and Founder of her own data as a service consultancy, Decide Data, which also provides 3rd party DAaaS (Data Analytics as a Service) solutions.

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

1. "If you don't know what you want, you're going to end up with a lot of what you don't want." This is especially true in collaborating with business stakeholders when it comes to data 😅
2. Focus on delivering value through data instead of delivering data and assuming it has value. – “Not all data is created equal.”
3. As a data leader, it's your role to help people figure out what they actually want by asking great questions and being a strong partner when it comes to the data/data work. Don't only focus on the data work itself but it's very easy to do data work for the sake of it instead of something that is valuable.
4. To deliver data work that actually moves the needle, we need to start from what are the key business processes and then understand the pain points and opportunities. Then, good data work is about how do we support and improve those business processes.
5. Relatedly, that's also the best way to drive exec alignment - talking about their business processes and how they can be improved first, data work second. They will feel seen and heard and are far more likely to lean in. At the end of the day addressing business and operational challenges is what data and analytics is all about.
6. Deliver something valuable early in any data collaboration with a business stakeholder. You don't have to deliver an entire completed project but time to first insight is time to value and you build momentum and credibility with that stakeholder.
7. At the beginning of a project - and delivering a data product is itself a project - you should work with stakeholders to not just define target outcomes...

Craziness of the overseas move (including a faulty office chair... long story) are to blame. Back to the normally scheduled one episode a week next week!

Episode list and links to all available episode transcripts here.

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.

Transcript for this episode (link) provided by Starburst. You can download their Data Products for Dummies e-book (info-gated) here and their Data Mesh for Dummies e-book (info gated) here.

Basten's LinkedIn: https://www.linkedin.com/in/basten-carmio-2585576/

In this episode, Scott interviewed Basten Carmio, Customer Delivery Architect of Data and Analytics at AWS Professional Services. To be clear, he was only representing his own views on the episode.

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

1. Your first use case - at the core - should A) deliver value in and of itself and B) improve your capabilities to deliver on incremental use cases. That's balancing value delivery, improving capabilities, and building momentum which are all key to a successful long-term mesh implementation.
2. When thinking about data mesh - or really any tech initiative - it's crucial to understand your starting state, not just your target end state. You need to adjust any approach to your realities and make incremental progress.
3. ?Controversial?: Relatedly, it's very important to define what success looks like. Doing data mesh cannot be the goal. You need to consider your maturity levels and where you want to focus and what will deliver value for your organization. That is different for each organization. Scott note: this shouldn't be controversial but many companies are not defining their mesh value bet…
4. Even aligning everyone on your organization's definition of mesh success will probably be hard. But it's important to do.
5. For a data mesh readiness assessment, consider where you can deliver incremental value and align it to your general business strategy. If you aren't ready to build incrementally, you aren't going to do well with data mesh.
6. A common value theme for data mesh implementations is easier collaboration across the organization through data; that leads to faster reactions to changes and opportunities in your markets. Mesh done well means it's far faster and easier for lines of business to collaborate with each other - especially in a reliable and scalable way - and there are far better standard rules/policies/ways of working around that collaboration. But organizations have to see value in that or there...