And they will ask the AI analyst for a report on the question, and the AI analyst will make them a fancy dashboard, and the AI manager won't be able to use it because they can't export it to Excel.
Great overview as always (I'm surprised you didn't said anything about dbt's new open source license that makes sure Snowflake can't run Fusion on their own compute).
My hunch on where this is going - data teams will have a deeper understanding that they exist to serve the business and will do EVERYTHING in their power to better understand the business and help the business users understand what they can do with the data.
All this tech doesn't help if the business users have no idea what to ask for.
BTW - a nice experiment to do is to look at the data, and use AI to come up with questions the data can answer, and then show that to a business user. So, instead of using AI to just answer questions, use it to think of questions to ask in the first place...
On dbt, I've never really understood why people are bothered by the licensing stuff to be honest. They are a business; we all know that; they have an obligation to survive as a business more than they have an obligation to give everyone free stuff. Plus, for Fusion, it's still free, unless you want to use it to compete against dbt. Which seems very reasonable to me - if you had a bar and said "to-go beers are free for everyone! Unless you open up a bar next to me, and use my to-go beers to get people to come into your bar instead of my bar," that would seem very sensible?
(Plus, the Snowflake/Fusion thing is clearly a bit more complicated than just "Snowflake can't use Fusion," because this: https://x.com/dbt_labs/status/1929979634646458873. I don't know what that means or how it works, but it seems dbt and Snowflake would rather work together on this than go Elon v Trump bloodbath.)
Anyway, on the more general point about where all this goes, I'm not sure I agree with that. If AI becomes more...agentic, it feels like data teals will spend less time on helping business people understand what's going on, and more time helping AIs understand. But in the latter case, "understand" just means pumping them full of more context, rather than explaining to them what it means. Which is at least a much easier problem. TBD if it's more valuable, I suppose.
I actually think the dbt move is the right one not just for dbt (who needs to make money, as you stated), but also the industry (the tech needs investment, ideally from a business that makes money off it). I don't fault them for it at all.
Wonderful post that gave me a flashback to the good 'ol Gateway conversations of the 19 whatevers. Or, was it IP Telephony? Wild rides are wild and wonderful. Thanks for the rememories.
Benn, I absolutely enjoy your posts and like the way they provoke to more thinking:).
I remember being shout at :))) by people when I said 5-7 years ago that all the self service analytics and better BI stack will lead nowhere as people actually have no idea how to correctly work with data or what to even look for, what questions to ask and why. Do not want to even start about the data literacy hype:). We move in tech circles, or maybe spirals if I am to be very optimistic.
Considering your previous post about “agency” and how many/most of us prefer to be told what to do, this one is a nice complement:))
Wonderfully written: “And then nobody does it. The dashboards go unfiltered; nobody drags; nothing is dropped; the only exploring anyone does is exporting to Excel.”
Will the AI Agent have an "export to CSV" tool?
If they don't, the AI support agents better get ready for a lot of AI tickets asking for it.
The AI backlog is already full, the AI manager will escalate to review priorities
And they will ask the AI analyst for a report on the question, and the AI analyst will make them a fancy dashboard, and the AI manager won't be able to use it because they can't export it to Excel.
Great overview as always (I'm surprised you didn't said anything about dbt's new open source license that makes sure Snowflake can't run Fusion on their own compute).
My hunch on where this is going - data teams will have a deeper understanding that they exist to serve the business and will do EVERYTHING in their power to better understand the business and help the business users understand what they can do with the data.
All this tech doesn't help if the business users have no idea what to ask for.
BTW - a nice experiment to do is to look at the data, and use AI to come up with questions the data can answer, and then show that to a business user. So, instead of using AI to just answer questions, use it to think of questions to ask in the first place...
On dbt, I've never really understood why people are bothered by the licensing stuff to be honest. They are a business; we all know that; they have an obligation to survive as a business more than they have an obligation to give everyone free stuff. Plus, for Fusion, it's still free, unless you want to use it to compete against dbt. Which seems very reasonable to me - if you had a bar and said "to-go beers are free for everyone! Unless you open up a bar next to me, and use my to-go beers to get people to come into your bar instead of my bar," that would seem very sensible?
(Plus, the Snowflake/Fusion thing is clearly a bit more complicated than just "Snowflake can't use Fusion," because this: https://x.com/dbt_labs/status/1929979634646458873. I don't know what that means or how it works, but it seems dbt and Snowflake would rather work together on this than go Elon v Trump bloodbath.)
Anyway, on the more general point about where all this goes, I'm not sure I agree with that. If AI becomes more...agentic, it feels like data teals will spend less time on helping business people understand what's going on, and more time helping AIs understand. But in the latter case, "understand" just means pumping them full of more context, rather than explaining to them what it means. Which is at least a much easier problem. TBD if it's more valuable, I suppose.
I actually think the dbt move is the right one not just for dbt (who needs to make money, as you stated), but also the industry (the tech needs investment, ideally from a business that makes money off it). I don't fault them for it at all.
I actually gasped at the "What????" link
The most shocking thing I've learned since finding out that suede is leather.
Wonderful post that gave me a flashback to the good 'ol Gateway conversations of the 19 whatevers. Or, was it IP Telephony? Wild rides are wild and wonderful. Thanks for the rememories.
Or maybe where IP part should fit into the ISO model.😜
Benn, I absolutely enjoy your posts and like the way they provoke to more thinking:).
I remember being shout at :))) by people when I said 5-7 years ago that all the self service analytics and better BI stack will lead nowhere as people actually have no idea how to correctly work with data or what to even look for, what questions to ask and why. Do not want to even start about the data literacy hype:). We move in tech circles, or maybe spirals if I am to be very optimistic.
Considering your previous post about “agency” and how many/most of us prefer to be told what to do, this one is a nice complement:))
Wonderfully written: “And then nobody does it. The dashboards go unfiltered; nobody drags; nothing is dropped; the only exploring anyone does is exporting to Excel.”