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#187 Maximizing the Value of Your Data Through Data Products - Interview w/ Bruno Aziza
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.
Bruno's LinkedIn: https://www.linkedin.com/in/brunoaziza/
Bruno's Medium: https://medium.com/@brunoaziza
Bruno's YouTube (Carcast videos): https://www.youtube.com/@brunoaziza
In this episode, Scott interviewed Bruno Aziza, Head of Data and Analytics at Google Cloud.
Some key takeaways/thoughts from Bruno's point of view:
- The end goal of your data strategy should be to reliably and scalably turn data into value. The best way to do that is by creating data products. How you get there might be different but don't lose focus on turning data into value.
- "The number one barrier to your ability to drive value of data is not your technology, it's your people and how you organize your team."
- Focus on the point of what you are trying to deliver, not the actual output. It's not about delivering a dashboard, it's about creating a sustainable way to explore, share, and consume information/insights, whatever form that takes.
- !Controversial!: There are 3 phases to getting to data driven; 1) is building a data lake or ocean, 2) is data mesh, and 3) is getting to a data product factory equivalent.
- It's easy to try to put the cart before the horse in data. Before doing something like data mesh, you have to think how you will develop data as a function in your organization.
- Understanding the data product manager role and leveraging data product managers well is crucial to building an effective data product strategy and practice. They are your data product CEOs.
- A CDO's effectiveness...
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By Data as a Product Podcast Network
5
99 ratings
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.
Bruno's LinkedIn: https://www.linkedin.com/in/brunoaziza/
Bruno's Medium: https://medium.com/@brunoaziza
Bruno's YouTube (Carcast videos): https://www.youtube.com/@brunoaziza
In this episode, Scott interviewed Bruno Aziza, Head of Data and Analytics at Google Cloud.
Some key takeaways/thoughts from Bruno's point of view:
- The end goal of your data strategy should be to reliably and scalably turn data into value. The best way to do that is by creating data products. How you get there might be different but don't lose focus on turning data into value.
- "The number one barrier to your ability to drive value of data is not your technology, it's your people and how you organize your team."
- Focus on the point of what you are trying to deliver, not the actual output. It's not about delivering a dashboard, it's about creating a sustainable way to explore, share, and consume information/insights, whatever form that takes.
- !Controversial!: There are 3 phases to getting to data driven; 1) is building a data lake or ocean, 2) is data mesh, and 3) is getting to a data product factory equivalent.
- It's easy to try to put the cart before the horse in data. Before doing something like data mesh, you have to think how you will develop data as a function in your organization.
- Understanding the data product manager role and leveraging data product managers well is crucial to building an effective data product strategy and practice. They are your data product CEOs.
- A CDO's effectiveness...