Why The Best Minds Of Our Generation Are Thinking About Click Ads
summary
Argues that ad tech created the best data tooling and culture but is now mostly an automated machine war; identifies the real data problem as change not scale; describes a Slack-built pipeline: a JavaScript ETL DSL parsed and executed by a Scala engine, backed by Kafka + Spark + Hive metastore, letting analysts write UDFs in JS, run locally, and auto-sync schemas to Hive; positions this as a pragmatic third way between SQL‑centric and JVM‑centric ETL.
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chapters (15)
- 0:00Introduction and speaker background
- 4:24Why ad tech attracts top talent
- 7:32The machine-dominated ad ecosystem
- 9:17Leaving ad tech for meaningful work
- 10:43The culture gap in non-ad tech
- 11:03Analytics engineering struggles
- 14:11The infinite loop of sadness
- 16:18First principles of data infrastructure
- 18:50ETL approaches at Facebook and Twitter
- 20:35The third way for data teams
- 22:43The real problem is change
- 23:26Inspiration from deep learning
- 25:30Slack’s ETL scripting language
- 27:56Harmonious data team collaboration
- 28:39Q&A session
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