zachrenwick.work
Data analytics engineer #SQL #DataModeling #Analytics #BigQuery #WebAnalytics
zachrenwick.work
51 posts
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147 following
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I agree but they've also been positioning Looker/BigQuery as a more open data stack recently. Specifically trying to market Looker modeler (the semantic layer part of Looker) as its own stand alone tool
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Yeah I've been following cube for a while now, lots of great new developments from their product, and love how they are breaking the metrics/semantic layer further out of the BI tools
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I never understood this, it's literally just extra lines of SQL code... because *reasons*
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There's so much value to add anywhere along the data chain.
Honestly, blending business context (analyst focus) with data modeling is an extremely impactful role.
Yes there's some shit AE models out there, but I've seen some terrible SQL written by data engineers too
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I tried that for Google Analytics 4 issues and it didnt work 😀
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2) Set up reverse ETL data feeds that power machine learning experiences on a website (fit predictor)
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1) Designed and built an ecommerce data mart from scratch, integrating GA4 and GA UA data to provide continuous web analytics reporting before and after the Universal Analytics sunset
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Integrate their product? Or buy the [future] competition?
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how is your neck not absolutely wrecked?
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Very often I will see heavy sampling.. like 2% of available data with GA4 explorations
We use the GA4 UI less and less.. and BigQuery / data mart is our "source of truth" for everything.
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damn I've found my people
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andddd that fixed our paid session count bug:
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I fixed it with this little bit of code:
CASE
WHEN REGEXP_CONTAINS(page_location, r'gclid=.+') AND traffic_source_source = 'google' THEN 'cpc'
/* Known GA4 misattribution bug */
ELSE traffic_source_medium
END
AS traffic_source_medium
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There were records where traffic source medium was "organic", even though that same hit contained a GCLID and the traffic_source name was 'google'
This should be impossible, as the GCLID would only populate on an ad (and therefore should be cpc/paid traffic source medium)
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Any data folks from bench accounting, feel free to reach out to me, we’ve got some data roles open in Vancouver
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Your longest ticket took you 48 days
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Oh damn there’s also this: github.com/hafenkran/du...
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One warning: if you are using events_ and events_intraday, prior day data can exist in both datasets for a certain amount of time. Had to build in logic to prefer full day export if exists (was not needed in GA UA)
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The native one (GA4 to BigQuery)?
Yes, for events_ and events_intraday (not accurate)
Have fun modelling sessions. The schema has also changed over time with new fields added
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The default chart look and feel is much better than I can do with Python. And frankly this workflow is just so much faster while still be reproducible (enough)
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I did something like:
with events_dates as (
select
distinct date
from
ga4_events
)
select
*
from
ga4_events
union all
select
*
from
events_fresh
left outer join
events_dates
on
events_fresh.event_date= events_dates .date
where events_dates .date is null
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Not disagreeing but one Grafana feature that looked v useful was the ability to define dashboards as code.
Tableau versioning and CI/CD is awful, are there other BI tools that are better on this front?
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Our federated data dept is 60+ ppl, so the specialization makes sense.
But I definitely see how you would want more of a generalist for smaller teams
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I think AE role being too narrrow depends on org and data team size. I’m an analytics engineer and there’s no shortage of work or value we can help push at the company.
I don’t handle ingestion but I model/transform/join everything from raw data to final BI/self serve datasets.
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BigQuery & dataform (like dbt but integrated into GCP)
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Strava guy!