[ahmedNarrator]

This is so great! You see exactly what we see and clearly you have shared similar experiences with dashboards not matching because of wrong table. (The good old "spent 3 weeks debugging an analysis using sales_data and then finally found that sales_data_v2 was built to solve it).

Yeah we do something very similar to dbt for taking restructuring the data into a single time-series table. We add things like identity resolution, diffing, incremental update and computing some cache columns.

Your Crystal Ball is SPOT ON!!! We get 3 kinds of data people. The ones who are like: "THIS WILL NEVER WORK", "Too bad I already built all this" or the "THIS IS THE FUTURE, HOW IS EVERYONE NOT USING IT".

I would love to chat and show you what we have (schedule a demo on our site and it will go to me and we can chat!)

Also, Teaser... When you standardize all of data and you create a consistent way to relating that standardized structure then analysis become very consistent. Imagine a world where your email attribution deep dive can be run by loading a template and point it to your "opened email" activity and your "order activity".... coming soon ... a Narrative Library.

[chrisjc]

> restructuring the data into a single time-series table. We add things like identity resolution, diffing, incremental update

So is this where the customer still has to do some work? Defining states and transforming their sources into a series of events with these states?

[cedricd]

Yes, the customer would have to define their activities (e.g. 'page view', 'completed order', 'support ticket opened') and write sql snippets to define them.

https://docs.narrator.ai/docs/activity-transformations describes these scripts and links to a few examples

[scapecast]

scheduled!