Cool. Rolling your own BI seems fraught with peril at most orgs where I imagine the buy vs build decision is always buy. How many PowerBI or Tableau seats do you need before rolling your own internal BI platform starts to make sense?
There are tons of data brokers that get near real time user level location data from mobile apps (usually not from ‘name brand’ apps but from the long tail) and then sell this as aggregated data products to others: eg https://docs.safegraph.com/docs/monthly-patterns .
Secondary sales and secondary sales rights generally impoverish the common engineer versus founders and exec management. It is extremely rare to find a scale-up that has had secondaries that put non-founder non-execs on equal footing. So sadly it is just business as usual in our industry.
I think similar to other situations e.g Starburst with Presto/Trino. There really are a limited number of devs pushing a long the core projects and a lot of people needing support. Each start up in the space can likely grow the pie for support and adoption and a few big enterprises will still hire in house devs.
This is a bizarrely misleading take from iOS 14 privacy labels. Use for ads optimization/measurement/targeting does not mean sharing with third parties for FB/IG or anyone who runs their own ads stack.
Databricks seems on a convergent evolution towards Snowflake, between the two of them I’d rather be starting at the position Snowflake is versus Databricks.
The CSAM numbers are presented awkwardly. The FB numbers suggest FB is way worse, but the FB and Twitter numbers are platform reported rather than externally identified.
FB and Twitter make more reports and publish more transparently. I’d also wager that reports = (all content #)(prevalence rate of CSAM)(detection sensitivity)*(reporting rate) and FB/TWTR probably have infinitely higher first terms, and better 3 and 4th terms in the equation.