I am happy, if embarrassed, to report that this wasn't working for me because I had a _space_ after my comma. "a+,+b" works. "a+, +b" does not work. ๐
I am happy, if embarrassed, to report that this wasn't working for me because I had a _space_ after my comma. "a+,+b" works. "a+, +b" does not work. ๐
Yeah, I have a comma! Removing the comma seems to show me the entire DAG, irrespective of the filters I inputted. Sounds like a ๐ indeed!
Okay, yes, this is similar to what I see. What I was expecting/hoping to see was this get limited to _only_ the models that are both downstream of `stg_tpcds_core__web_sales` _and_ upstream of `transactions`.
no :(
when I try model_a+,+model_b, I see more than just the intersection. I see everything upstream of model_b!
yes, exactly!!
I wish there was a way for the dbt Cloud Explore DAG to filter to content that exists *between* two nodes. Anyone know of a fun work-around for this with other tools?
#dataBS
this is the 10x analytics engineering you hired me for, E
become hello kitty. become ungovernable.
a poem by poetry:
poetry run dbt compile
command not found: dbt
poetry show | grep dbt
dbt 1.0.0.38.22
pip freeze | grep dbt
dbt==1.0.0.38.22
which dbt
dbt not found
(look, no one said it was a happy poem)
#dataBS
It's fun to work on challenging problems.
It's *more* fun to work on them as a team.
It's the *most* fun when you have a smart teammate who finally cracks the code.
Data is a team sport!
#dataBS
dbt job: "Can't parse a JSON blob, I'm out."
me: *looks for a needle in the 100M-row haystack*
me: "Aha! This looks fine? Guess I'll paste it in a text editor to double check."
text editor: "Uh, boss"
me: "Is that...is that a tiny red 'BS'?"
BS broke my data. I can't make this shit up.
#dataBS
our team motto is famously "naming things is hard"
Life is messy. So is analytics engineering. Sometimes your warehouse looks like the "clothes pile" your partner has been slowly building in the corner of your closet.
The good news is that you CAN make your warehouse a wareHOME. And that I wrote you a how-to guide.
tinyurl.com/5h35ktj2 #dataBS
pies > pie charts
10x analytics engineering tip for the week of Thanksgiving: If you're stuck on a problem, let its solution bake in the recesses of your mind while you bake an actual pie. Whether the solution comes to you matters not, because it's a holiday week. And you end up with pie. #dataBS
I am convinced that the YML-based semantic layer was as much invented by a data professional as the stiletto heel was invented by a woman
(the stiletto heel was invented by a man)
#dataBS
we are so here
also winnie tksm, your guide was so helpful ๐
HI PEDRAM
Do I know anyone in #dataBS who has built out a fairly full-scale metrics layer in MetricFlow (dbt) or Cube? Looking for someone who'd connect for ~30 with someone on my team starting the process for us at Hex!
is this where data twitter went?