Sign up to save your podcasts
Or
Share #183 Business Intelligence's Place in Data Mesh - BI-gin With the End in Mind - Interview w/ Ryan Dolley
Share to email
Share to Facebook
Share to X
Share to email
Share to Facebook
Share to X
Or
#183 Business Intelligence's Place in Data Mesh - BI-gin With the End in Mind - Interview w/ Ryan Dolley
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.
Ryan's LinkedIn: https://www.linkedin.com/in/ryandolley/
In this episode, Scott interviewed Ryan Dolley, an Independent Business Intelligence (BI) Consultant.
Before we jump in, lots of things in the key takeaways are marked as potentially controversial. Because much of what Ryan covered hasn't really been stated by a lot of people. So until we have more consensus, of course things _could_ be controversial.
Some key takeaways/thoughts from Ryan's point of view:
- Begin with the end in mind. It's easy to lose focus on what you are trying to accomplish instead of what steps you are taking. Focus on what the target outcome is and use that as a North Star to measure if you need to course correct.
- BI people need to brace themselves for a wave of innovation coming. There is so much - hopefully positive - change coming up the stack and BI people can embrace it or get washed over by the wave. Embrace and ride that wave and upskill!
- ?Controversial?: Data mesh - and just about every other paradigm - does not focus enough on the last mile of analytics, at least not explicitly. So we need to get a lot more specific about what is necessary to actually take advantage of upstream improvements in data to deliver better analytics.
- !Important!: We need to get more specific on who does cross-domain BI in a decentralized world. Otherwise, we have interoperable data but no one specifically leveraging that interoperability for improving our understanding of the overall organization.
- BI as a practice needs to be much better at understanding and implementing iterative feedback. It's not been part of the playbook to date.
- ?Controversial?: If domains develop BI...
View all episodes
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.
Ryan's LinkedIn: https://www.linkedin.com/in/ryandolley/
In this episode, Scott interviewed Ryan Dolley, an Independent Business Intelligence (BI) Consultant.
Before we jump in, lots of things in the key takeaways are marked as potentially controversial. Because much of what Ryan covered hasn't really been stated by a lot of people. So until we have more consensus, of course things _could_ be controversial.
Some key takeaways/thoughts from Ryan's point of view:
- Begin with the end in mind. It's easy to lose focus on what you are trying to accomplish instead of what steps you are taking. Focus on what the target outcome is and use that as a North Star to measure if you need to course correct.
- BI people need to brace themselves for a wave of innovation coming. There is so much - hopefully positive - change coming up the stack and BI people can embrace it or get washed over by the wave. Embrace and ride that wave and upskill!
- ?Controversial?: Data mesh - and just about every other paradigm - does not focus enough on the last mile of analytics, at least not explicitly. So we need to get a lot more specific about what is necessary to actually take advantage of upstream improvements in data to deliver better analytics.
- !Important!: We need to get more specific on who does cross-domain BI in a decentralized world. Otherwise, we have interoperable data but no one specifically leveraging that interoperability for improving our understanding of the overall organization.
- BI as a practice needs to be much better at understanding and implementing iterative feedback. It's not been part of the playbook to date.
- ?Controversial?: If domains develop BI...