It's undoubtedly a good news for data analytics teams!
In the alternatives for semantic layers, cube.dev is a strong one and all features are available in the open source offering as well. I have recently deployed it in production, and am happy with it.
Have you heard of them? What's your view on them vs Transform metrics layer?
Hi David, I have to say I am excited as well, though the last sentence really resonated in me - what about the dependence on dbt cloud? How big lock-in is this?
Furthermore what this means for the ecosystem? Will other data tools be able to integrate with the metric definitions, generate and query them? Offer alternative processing/caching?
Is there a good video of someone defining, using and reusing a metric somewhere? I have tried to wrap my head around the concept for a while, but I don’t understand how something can be both complex enough to need abstraction and generic enough that it can be widely reused. I know I’m missing something.
It's undoubtedly a good news for data analytics teams!
In the alternatives for semantic layers, cube.dev is a strong one and all features are available in the open source offering as well. I have recently deployed it in production, and am happy with it.
Have you heard of them? What's your view on them vs Transform metrics layer?
I missed the Transform news. Very, very interesting.
Hi David, I have to say I am excited as well, though the last sentence really resonated in me - what about the dependence on dbt cloud? How big lock-in is this?
Furthermore what this means for the ecosystem? Will other data tools be able to integrate with the metric definitions, generate and query them? Offer alternative processing/caching?
Is there a good video of someone defining, using and reusing a metric somewhere? I have tried to wrap my head around the concept for a while, but I don’t understand how something can be both complex enough to need abstraction and generic enough that it can be widely reused. I know I’m missing something.