Causal Inference for Product Decisions
Moving teams beyond correlation dashboards to causal models that actually inform decisions.
Edition 8 · 2024
Seattle, WASeattle Convention Center
July 15–17, 2024
8,900
Attendees
142
Talks
63
Papers
Headliners
Moving teams beyond correlation dashboards to causal models that actually inform decisions.
How cost-based optimizers are being rebuilt for Iceberg, Delta, and the disaggregated stack.
Keeping operational databases and the lakehouse in sync without melting the source system.
A governance framework that gives finance and engineering one shared, real-time view of spend.
The tooling, runbooks, and incentives that keep data products dependable and engineers rested.
A practical framework for building evaluation suites that catch real regressions, not vibes.
Design tradeoffs in LSM trees, replication, and consensus for databases that span continents.
Connecting data platforms across providers without opening holes your security team will hate.
Lessons from running mission-critical streaming pipelines with strict ordering and replay guarantees.
Why most ML benchmarks mislead, and how to build evaluation suites that survive contact with reality.
Proceedings
E. Larsen, D. Ramirez
L. Zhao, K. Nakamura
E. Larsen, P. Adeyemi
C. Mendez, I. Santos
L. Zhao, B. Andersen
Y. Patel, U. Johansson
K. Nakamura, F. Almeida
S. Volkov, D. Chen
P. Adeyemi, W. Kim
C. Williams, H. Tanaka
T. Han, G. Park
L. Zhao, Q. Zhang
V. Cruz, B. Andersen